Collaborative Multi-User Virtual Reality

Abstract

The present application discloses collaborative multi-user virtual reality. Embodiments of a graphics device may include: a processor; a memory communicatively coupled to the processor; and a collaboration engine communicatively coupled to the processor for identifying shared graphics components between two or more users in an environment, and sharing the shared graphics components with the two or more users in the environment. Embodiments of the collaboration engine may include one or more of a centralized sharer, a depth sharer, a shared preprocessor, a multi-port graphics subsystem, and a decoding sharer. Other embodiments are disclosed and claimed.

Description

Technical Field

[0001] Embodiments relate generally to data processing and to graphics processing via a graphics processing unit. More specifically, embodiments relate to collaborative multi-user virtual reality (VR). Background Art

[0002] Current parallel graphics data processing includes systems and methods developed to perform specific operations on graphics data, such as linear interpolation, tessellation, rasterization, texture mapping, depth testing, etc. Traditionally, graphics processors use fixed-function compute units to process graphics data; however, recently, portions of graphics processors have become programmable, enabling such processors to support a wide variety of operations for processing vertex and fragment data. Graphics processors can be used in a variety of VR applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0003] Various advantages of the embodiments will become apparent to those skilled in the art from a reading of the following description and appended claims, and from reference to the following drawings, in which:

[0004] Figure 1 is a block diagram illustrating a computer system configured to implement one or more aspects of the embodiments described herein;

[0005] Figures 2A to 2D A parallel processor component according to an embodiment is shown;

[0006] FIG. 3A to FIG. 3B is a block diagram of a graphics multiprocessor according to an embodiment;

[0007] FIG. 4A to FIG. 4F An exemplary architecture is presented in which a plurality of GPUs are communicatively coupled to a plurality of multi-core processors;

[0008] Figure 5 Demonstrating a graphics processing pipeline according to an embodiment;

[0009] Fig. 6A is a block diagram of an example of an electronic processing system according to an embodiment;

[0010] Figure 6B is a block diagram of an example of a sensing engine according to an embodiment;

[0011] Figure 6C is a block diagram of an example of a focus engine according to an embodiment;

[0012] Fig.6D is a block diagram of an example of a motion engine according to an embodiment;

[0013] Fig. 6E is a block diagram of an example of a collaboration engine according to an embodiment;

[0014] Fig. 6F is a block diagram of an example of a graphics device according to an embodiment;

[0015] FIG. 6G to FIG. 6L is a flowchart of an example of a method of graphical collaboration according to an embodiment;

[0016] Figure 6M is a block diagram of another example of a graphics device according to an embodiment;

[0017] Figure 6N is a flowchart of another example of a method of graphic collaboration according to an embodiment;

[0018] Fig. 7A is a block diagram of an example of a centralized sharer according to an embodiment;

[0019] Fig. 8A is a block diagram of an example of a depth sharer according to an embodiment;

[0020] Figure 8B is a schematic diagram of an example of a user in an AR / VR environment according to an embodiment;

[0021] Figure 8C is a block diagram of an example of a shared pre-processor according to an embodiment;

[0022] Fig.8D is a schematic diagram of another example of a user in an AR / VR environment according to an embodiment;

[0023] Fig.9A is a block diagram of an example of a multi-port graphics subsystem according to an embodiment;

[0024] Fig. 9B is a block diagram of another example of a multi-port graphics subsystem according to an embodiment;

[0025] Fig. 9C is a block diagram of another example of a multi-port graphics subsystem according to an embodiment;

[0026] Fig. 10A is a block diagram of an example of a shared decoder according to an embodiment;

[0027] Fig. 10B is a block diagram of another example of a multi-port graphics subsystem according to an embodiment;

[0028] Fig. 10C is a schematic diagram of an example of 360 frames according to an embodiment;

[0029] Fig. 10D is another schematic diagram of an example of a 360-frame according to an embodiment;

[0030] Fig.11 is a diagram of an example of a head mounted display (HMD) system according to an embodiment;

[0031] Fig.12 According to the embodiment, it includes Fig.11 A block diagram of an example of functional components in an HMD system;

[0032] Fig.13 is a block diagram of an example of a general processing cluster included in a parallel processing unit according to an embodiment;

[0033] Fig.14 is a conceptual diagram of an example of a graphics processing pipeline that may be implemented within a parallel processing unit according to an embodiment;

[0034] Fig.15 is a block diagram of an example of a streaming multiprocessor according to an embodiment;

[0035] Figure 16 to Figure 18 is a block diagram of an example of an overview of a data processing system according to an embodiment;

[0036] Fig.19 is a block diagram of an example of a graphics processing engine according to an embodiment;

[0037] Figure 20 to Figure 22 is a block diagram of an example of an execution unit according to an embodiment;

[0038] Fig.23 is a block diagram of an example of a graphics pipeline according to an embodiment;

[0039] FIG. 24A to FIG. 24B is a block diagram of an example of a graphics pipeline according to an embodiment;

[0040] Fig.25 is a block diagram of an example of a graphics software architecture according to an embodiment;

[0041] Fig.26 is a block diagram of an example of an intellectual property (IP) core development system according to an embodiment; and

[0042] Fig. 27 is a block diagram of an example of a system on chip integrated circuit according to an embodiment. DETAILED DESCRIPTION

[0043] In the following description, many details are set forth to provide a more comprehensive understanding of the present disclosure. However, it is apparent to those skilled in the art that the present invention can be practiced without one or more of these specific details. In other examples, well-known features are not described so as not to hinder the present invention.

[0044] System Overview

[0045] Figure 1 1 is a block diagram illustrating a computing system 100 that is configured to implement one or more aspects of the embodiments described herein. The computing system 100 includes a processing subsystem 101 having one or more processors 102 and a system memory 104 that communicate with the system memory via an interconnect path that may include a memory hub 105. The memory hub 105 may be a separate component within a chipset component, or may be integrated within one or more processors 102. The memory hub 105 is coupled to an I / O subsystem 111 via a communication link 106. The I / O subsystem 111 includes an I / O hub 107 that may enable the computing system 100 to receive input from one or more input devices 108. Additionally, the I / O hub 107 may enable a display controller that may be included in one or more processors 102 to provide output to one or more display devices 110A. In one embodiment, the one or more display devices 110A coupled to the I / O hub 107 may include local, internal, or embedded display devices.

[0046] In one embodiment, the processing subsystem 101 includes one or more parallel processors 112, which are coupled to the memory hub 105 via a bus or other communication link 113. The communication link 113 can be one of any number of standard-based communication link technologies or protocols (such as, but not limited to, the PCI Express bus), or can be a vendor-specific communication interface or communication structure. In one embodiment, the one or more parallel processors 112 form a computationally focused parallel or vector processing system that includes a large number of processing cores and / or processing clusters (such as, for example, an integrated many-core (MIC) processor). In one embodiment, the one or more parallel processors 112 form a graphics processing subsystem that can output pixels to one of one or more display devices 110A coupled via the I / O hub 107. The one or more parallel processors 112 may also include a display controller and display interface (not shown) to enable direct connection to one or more display devices 110B.

[0047] Within the I / O subsystem 111, a system storage unit 114 may be connected to the I / O hub 107 to provide a storage mechanism for the computing system 100. An I / O switch 116 may be used to provide an interface mechanism to enable connection between the I / O hub 107 and other components, such as a network adapter 118 and / or a wireless network adapter 119 that may be integrated into the platform, and various other devices that may be added via one or more plug-in devices 120. The network adapter 118 may be an Ethernet adapter or another wired network adapter. The wireless network adapter 119 may include one or more of the following: Wi-Fi, Bluetooth, near field communication (NFC), or other network devices including one or more radio devices.

[0048] The computing system 100 may include other components not explicitly shown, including USB or other port connections, optical storage drives, video capture devices, etc., which may also be connected to the I / O hub 107. Figure 1 The communication paths interconnecting the various components in the system may be implemented using any suitable protocol, such as a PCI (Peripheral Component Interconnect) based protocol (e.g., PCI Express bus) or any other bus or point-to-point communication interface and / or protocol (e.g., NV-Link high-speed interconnect, or interconnect protocols known in the art).

[0049] In one embodiment, one or more parallel processors 112 include circuits optimized for graphics and video processing (including, for example, video output circuits) and constitute a graphics processing unit (GPU). In another embodiment, one or more parallel processors 112 include circuits optimized for general-purpose processing while maintaining the underlying computing architecture described in more detail herein. In yet another embodiment, the components of the computing system 100 may be integrated on a single integrated circuit along with one or more other system elements. For example, one or more parallel processors 112, memory hub 105, processor 102, and I / O hub 107 may be integrated into a system on a chip (SoC) integrated circuit. Alternatively, the components of the computing system 100 may be integrated into a single package to form a system in package (SIP) configuration. In one embodiment, at least a portion of the components of the computing system 100 may be integrated into a multi-chip module (MCM), which may be interconnected with other multi-chip modules into a modular computing system.

[0050] It will be appreciated that the computing system 100 shown herein is illustrative and that various variations and modifications are possible. The connection topology, including the number and rows of bridges, the number of processor(s) 102, and the number of parallel processor(s) 112, may be modified as desired. For example, in some embodiments, the system memory 104 is connected to the processor(s) 102 directly rather than through a bridge, while other devices communicate with the system memory 104 via the memory hub 105 and the processor(s) 102. In other alternative topologies, the parallel processor(s) 112 are connected to the I / O hub 107 or directly to one of the one or more processors 102, rather than to the memory hub 105. In other embodiments, the I / O hub 107 and the memory hub 105 may be integrated into a single chip. Some embodiments may include two or more groups of processors 102 attached via multiple sockets, which may be coupled to two or more instances of the parallel processor(s) 112.

[0051] Some specific components shown herein are optional and may not be included in all implementations of computing system 100. For example, any number of plug-in cards or peripherals may be supported, or some components may be eliminated. In addition, some architectures may be different from those described above. Figure 1 Different terminology is used for components similar to those shown in FIG. 1. For example, in some architectures, memory hub 105 may be referred to as a north bridge, while I / O hub 107 may be referred to as a south bridge.

[0052] Figure 2A A parallel processor 200 is shown according to an embodiment. The various components of the parallel processor 200 may be implemented using one or more integrated circuit devices, such as a programmable processor, an application specific integrated circuit (ASIC), or a field programmable gate array (FPGA). According to an embodiment, the parallel processor 200 shown is Figure 1 A variation of one or more parallel processors 112 is shown in .

[0053] In one embodiment, parallel processor 200 includes parallel processing unit 202. The parallel processing unit includes an I / O unit 204, which enables communication with other devices (including other instances of parallel processing unit 202). I / O unit 204 can be directly connected to other devices. In one embodiment, I / O unit 204 is connected to other devices via the use of a hub or switch interface (e.g., memory hub 105). The connection between memory hub 105 and I / O unit 204 forms communication link 113. Within parallel processing unit 202, I / O unit 204 is connected to host interface 206 and memory crossbar 216, wherein host interface 206 receives commands related to performing processing operations and memory crossbar 216 receives commands related to performing memory operations.

[0054] When the host interface 206 receives the command buffer via the I / O unit 204, the host interface 206 can direct the work operations for executing those commands to the front end 208. In one embodiment, the front end 208 is coupled with a scheduler 210, which is configured to distribute commands or other work items to the processing cluster array 212. In one embodiment, the scheduler 210 ensures that the processing cluster array 212 is properly configured and in a valid state before the task is distributed to the processing clusters of the processing cluster array 212. In one embodiment, the scheduler 210 is implemented via firmware logic executed on a microcontroller. The microcontroller-implemented scheduler 210 can be configured to perform complex scheduling and work distribution operations at coarse and fine granularity, thereby achieving fast preemption and context switching of threads executed on the processing array 212. In one embodiment, the host software can prove the workload for scheduling on the processing array 212 via one of a plurality of image processing doorbells. The workload can then be automatically distributed across the processing array 212 by the scheduler 210 logic within the scheduler microcontroller.

[0055] The processing cluster array 212 may include up to "N" processing clusters (e.g., cluster 214A, cluster 214B, up to cluster 214N). Each cluster 214A-214N of the processing cluster array 212 may execute a large number of concurrent threads. The scheduler 210 may use various scheduling and / or work distribution algorithms to assign work to the clusters 214A-214N of the processing cluster array 212, which may vary depending on the workload generated for each type of program or calculation. Scheduling may be handled dynamically by the scheduler 210, or may be partially assisted by compiler logic during the compilation of program logic configured for execution by the processing cluster array 212. In one embodiment, different clusters 214A-214N of the processing cluster array 212 may be assigned to process different types of programs, or to perform different types of calculations.

[0056] Processing cluster array 212 may be configured to perform various types of parallel processing operations. In one embodiment, processing cluster array 212 is configured to perform general-purpose parallel computing operations. For example, processing cluster array 212 may include logic for performing processing tasks including filtering video and / or audio data, performing modeling operations (including physics operations), and performing data transformations.

[0057] In one embodiment, processing cluster array 212 is configured to perform parallel graphics processing operations. In embodiments where parallel processor 200 is configured to perform graphics processing operations, processing cluster array 212 may include additional logic for supporting the execution of such graphics processing operations, including but not limited to texture sampling logic for performing texture operations, and tessellation logic and other vertex processing logic. In addition, processing cluster array 212 may be configured to execute shader programs related to graphics processing, such as but not limited to vertex shaders, tessellation shaders, geometry shaders, and pixel shaders. Parallel processing unit 202 may pass data from system memory via I / O unit 204 for processing. During processing, the passed data may be stored in on-chip memory (e.g., parallel processor memory 222) during processing and then written back to system memory.

[0058] In one embodiment, when the parallel processing unit 202 is used to perform graphics processing, the scheduler 210 can be configured to divide the processing workload into tasks of approximately equal size to better enable the distribution of graphics processing operations to multiple clusters 214A to 214N in the processing cluster array 212. In some embodiments, multiple portions of the processing cluster array 212 can be configured to perform different types of processing. For example, a first portion can be configured to perform vertex shading and topology generation, a second portion can be configured to perform tessellation and geometry shading, and a third portion can be configured to perform pixel shading or other screen space operations to generate a rendered image for display. Intermediate data generated by one or more of the clusters 214A to 214N can be stored in a buffer to allow the intermediate data to be transmitted between the clusters 214A to 214N for further processing.

[0059] During operation, the processing cluster array 212 may receive processing tasks to be performed via the scheduler 210, which receives commands defining the processing tasks from the front end 208. For graphics processing operations, the processing tasks may include indices of data to be processed (e.g., surface (patch) data, primitive data, vertex data, and / or pixel data) as well as state parameters and commands defining how the data is to be processed (e.g., what program to execute). The scheduler 210 may be configured to obtain indices corresponding to the tasks, or may receive these indices from the front end 208. The front end 208 may be configured to ensure that the processing cluster array 212 is configured to a valid state before initiating a workload specified by an incoming command buffer (e.g., a batch buffer, a push buffer, etc.).

[0060] Each of the one or more instances of the parallel processing unit 202 can be coupled to a parallel processor memory 222. The parallel processor memory 222 can be accessed via a memory crossbar switch 216, which can receive memory requests from the processing cluster array 212 and the I / O unit 204. The memory crossbar switch 216 can access the parallel processor memory 222 via a memory interface 218. The memory interface 218 can include a plurality of partition units (e.g., partition unit 220A, partition unit 220B, up to partition unit 220N), each of which can be coupled to a portion of the parallel processor memory 222 (e.g., a memory unit). In one implementation, the number of partition units 220A-220N is configured to be equal to the number of memory units, such that the first partition unit 220A has a corresponding first memory unit 224A, the second partition unit 220B has a corresponding memory unit 224B, and the Nth partition unit 220N has a corresponding Nth memory unit 224N. In other embodiments, the number of partition units 220A-220N may not be equal to the number of memory devices.

[0061] In various embodiments, the memory units 224A to 224N may include various types of memory devices, including dynamic random access memory (DRAM) or graphics random access memory (e.g., synchronous graphics random access memory (SGRAM), including graphics double data rate (GDDR) memory). In one embodiment, the memory units 224A to 224N may also include 3D stacked memory, including but not limited to high bandwidth memory (HBM). Those skilled in the art will recognize that the specific implementation of the memory units 224A to 224N may vary and may be selected from one of a variety of conventional designs. Render targets (e.g., frame buffers or texture maps) may be stored across the memory units 224A to 224N, allowing the partition units 220A to 220N to write multiple portions of each render target in parallel to efficiently use the available bandwidth of the parallel processor memory 222. In some embodiments, local instances of the parallel processor memory 222 may be excluded to facilitate utilizing a unified memory design of the system memory in conjunction with local cache memory.

[0062] In one embodiment, any of the clusters 214A-214N of the processing cluster array 212 can process data to be written to any of the memory units 224A-224N within the parallel processor memory 222. The memory crossbar 216 can be configured to pass the output of each cluster 214A-214N to any partition unit 220A-220N or another cluster 214A-214N that can perform additional processing operations on the output. Each cluster 214A-214N can communicate with the memory interface 218 through the memory crossbar 216 to read from or write to various external memory devices. In one embodiment, the memory crossbar 216 has a connection to the memory interface 218 to communicate with the I / O unit 204 and has a connection to the local instance of the parallel processor memory 222, thereby enabling the processing units within the different processing clusters 214A-214N to communicate with the system memory or other memory that is not local to the parallel processing unit 202. In one embodiment, the memory crossbar switch 216 may use virtual channels to separate traffic flows between the clusters 214A-214N and the partition units 220A-220N.

[0063] Although a single instance of parallel processing unit 202 is shown in parallel processor 200, any number of instances of parallel processing unit 202 may be included. For example, multiple instances of parallel processing unit 202 may be provided on a single plug-in card, or multiple plug-in cards may be interconnected. Different instances of parallel processing unit 202 may be configured to interoperate even if these different instances have different numbers of processing cores, different amounts of local parallel processor memory and / or other configuration differences. For example and in one embodiment, some instances of parallel processing unit 202 may include higher precision floating point units relative to other instances. The system including one or more instances of parallel processing unit 202 or parallel processor 200 may be implemented with multiple configurations and form factors, including but not limited to desktop, laptop or handheld personal computers, servers, workstations, game consoles and / or embedded systems.

[0064] Figure 2B is a block diagram of a partition unit 220 according to an embodiment. In one embodiment, the partition unit 220 is Figure 2A2 is an example of one of the partition units 220A to 220N of the memory crossbar 216. As shown, the partition unit 220 includes an L2 cache 221, a frame buffer interface 225, and an ROP 226 (raster operation unit). The L2 cache 221 is a read / write cache that is configured to perform load and store operations received from the memory crossbar switch 216 and the ROP 226. Read misses and urgent write-back requests are output by the L2 cache 221 to the frame buffer interface 225 for processing. Updates may also be sent to the frame buffer via the frame buffer interface 225 for processing. In one embodiment, the frame buffer interface 225 interfaces with one of the memory units in the parallel processor memory (e.g., the memory units 224A to 224N of FIG. 2 (e.g., within the parallel processor memory 222)).

[0065] In graphics applications, ROP 226 is a processing unit that performs raster operations such as stencil, z-test, blending, etc. ROP 226 then outputs processed graphics data that is stored in graphics memory. In some embodiments, ROP 226 includes compression logic that compresses depth or color data written to memory and decompresses depth or color data read from memory. The compression logic can be lossless compression logic that utilizes one or more of a variety of compression algorithms. The type of compression performed by ROP 226 can vary based on the statistical characteristics of the data to be compressed. For example, in one embodiment, delta color compression is performed on depth and color data on a tile-by-tile basis.

[0066] In some embodiments, ROP 226 is included within each processing cluster (e.g., clusters 214A to 214N of FIG. 2 ) rather than within partition unit 220. In such embodiments, read and write requests for pixel data rather than pixel fragment data are transmitted via memory crossbar 216. The processed graphics data may be displayed on a display device (e.g., Figure 1 100), is routed for further processing by the processor(s) 102, or is routed for processing by the processor(s) 102. Figure 2A The process is further processed by one of the processing entities within the parallel processor 200.

[0067] Figure 2CIt is a block diagram of a processing cluster 214 in a parallel processing unit according to an embodiment. In one embodiment, the processing cluster is an instance of one of the processing clusters 214A to 214N of Figure 2. The processing cluster 214 can be configured to execute many threads in parallel, wherein the term "thread" refers to an instance of a specific program executed on a set of specific input data. In some embodiments, in the case where multiple independent instruction units are not provided, a single instruction multiple data (SIMD) instruction issuance technology is used to support the parallel execution of a large number of threads. In other embodiments, in the case of using a common instruction unit, a single instruction multiple thread (SIMT) technology is used to support the parallel execution of a large number of generally synchronized threads, and the common instruction unit is configured to issue instructions to a group of processing engines in each of the processing clusters. Different from the SIMD execution regime (wherein, all processing engines usually execute the same instruction), SIMT execution allows different threads to more easily pass through a given thread program along divergent execution paths. It will be understood by those skilled in the art that the SIMD processing regime represents a functional subset of the SIMT processing regime.

[0068] The operation of the processing cluster 214 can be controlled via a pipeline manager 232, which distributes processing tasks to SIMT parallel processors. The pipeline manager 232 receives instructions from the scheduler 210 of Figure 2, and manages the execution of those instructions via a graphics multiprocessor 234 and / or a texture unit 236. The graphics multiprocessor 234 shown is an exemplary instance of a SIMT parallel processor. However, various types of SIMT parallel processors with different architectures may be included in the processing cluster 214. One or more instances of the graphics multiprocessor 234 may be included in the processing cluster 214. The graphics multiprocessor 234 may process data, and a data crossbar 240 may be used to distribute the processed data to one of a plurality of possible destinations (including other shader units). The pipeline manager 232 may facilitate the distribution of the processed data by specifying the destination of the processed data to be distributed via the data crossbar 240.

[0069] Each graphics multiprocessor 234 within a processing cluster 214 may include an identical set of function execution logic (e.g., arithmetic logic units, load-store units, etc.). The function execution logic may be configured in a pipelined manner in which a new instruction may be issued before a previous instruction is completed. The function execution logic supports a wide variety of operations including integer and floating point arithmetic, comparison operations, Boolean operations, bit shifts, and calculation of various algebraic functions. In one embodiment, the same functional unit hardware may be utilized to perform different operations, and any combination of functional units may be present.

[0070] The instructions transmitted to the processing cluster 214 constitute threads. A group of threads that are executed across a group of parallel processing engines is a thread group. A thread group executes the same program on different input data. Each thread in a thread group can be assigned to a different processing engine in the graphics multiprocessor 234. A thread group may include fewer threads than the number of processing engines in the graphics multiprocessor 234. When a thread group includes fewer threads than the number of processing engines, one or more of the processing engines may be idle during the cycle when the thread group is being processed. A thread group may also include more threads than the number of processing engines in the graphics multiprocessor 234. When a thread group includes more threads than the number of processing engines in the graphics multiprocessor 234, processing may be performed on consecutive clock cycles. In one embodiment, multiple thread groups may be executed concurrently on the graphics multiprocessor 234.

[0071] In one embodiment, the graphics multiprocessor 234 includes an internal cache memory to perform load and store operations. In one embodiment, the graphics multiprocessor 234 can abandon the internal cache and use the cache memory (e.g., L1 cache 308) within the processing cluster 214. Each graphics multiprocessor 234 also has access to the L2 cache within the partition unit (e.g., partition units 220A to 220N of Figure 2) that is shared among all processing clusters 214 and can be used to transfer data between threads. The graphics multiprocessor 234 can also access off-chip global memory, which can include one or more of the local parallel processor memory and / or system memory. Any memory outside the parallel processing unit 202 can be used as global memory. Multiple embodiments (wherein the processing cluster 214 includes multiple instances of the graphics multiprocessor 234) can share common instructions and data, which can be stored in the L1 cache 308.

[0072] Each processing cluster 214 may include an MMU 245 (memory management unit) configured to map virtual addresses into physical addresses. In other embodiments, one or more instances of the MMU 245 may reside within the memory interface 218 of FIG. 2 . The MMU 245 includes: a set of page table entries (PTEs) for mapping virtual addresses of tiles (more on tiling) to physical addresses; and optionally a cache line index. The MMU 245 may include an address translation lookaside buffer (TLB) or cache that may reside within the graphics multiprocessor 234 or L1 cache or processing cluster 214. Physical addresses are processed to distribute surface data access locality, thereby allowing efficient request interleaving among partition units. The cache line index can be used to determine whether a request for a cache line is a hit or a miss.

[0073] In graphics and computing applications, the processing clusters 214 may be configured such that each graphics multiprocessor 234 is coupled to a texture unit 236 for performing texture mapping operations, such as determining texture sample locations, reading texture data, and filtering texture data. Texture data is read from an internal texture L1 cache (not shown) or in some embodiments from an L1 cache within the graphics multiprocessor 234, and retrieved from an L2 cache, local parallel processor memory, or system memory, as needed. Each graphics multiprocessor 234 outputs processed tasks to a data crossbar 240 to provide the processed tasks to another processing cluster 214 for further processing or to store the processed tasks in an L2 cache, local parallel processor memory, or system memory via a memory crossbar 216. The preROP 242 (e.g., pre-raster operation unit) is configured to receive data from the graphics multiprocessor 234, direct the data to ROP units, which may be located with partition units (e.g., partition units 220A to 220N of FIG. 2 ) as described herein. The preROP 242 unit may perform optimizations for color blending, organize pixel color data, and perform address translations.

[0074] It will be appreciated that the core architecture described herein is illustrative and that various variations and modifications are possible. Any number of processing units (e.g., graphics multiprocessor 234, texture unit 236, preROP 242, etc.) may be included within processing cluster 214. Furthermore, while only one processing cluster 214 is shown, a parallel processing unit as described herein may include any number of instances of processing cluster 214. In one embodiment, each processing cluster 214 may be configured to operate independently of other processing clusters 214 using separate and distinct processing units, L1 caches, etc.

[0075] Figure 2D A graphics multiprocessor 234 is shown according to one embodiment. In such an embodiment, the graphics multiprocessor 234 is coupled to the pipeline manager 232 of the processing cluster 214. The graphics multiprocessor 234 has an execution pipeline including, but not limited to, an instruction cache 252, an instruction unit 254, an address mapping unit 256, a register file 258, one or more general purpose graphics processing unit (GPGPU) cores 262, and one or more load / store units 266. The GPGPU cores 262 and the load / store units 266 are coupled to a cache memory 272 and a shared memory 270 via a memory and cache interconnect 268.

[0076] In one embodiment, the instruction cache 252 receives a stream of instructions to be executed from the pipeline manager 232. These instructions are cached in the instruction cache 252 and dispatched by the instruction unit 254 for execution. The instruction unit 254 can dispatch instructions into thread groups (e.g., warps), where each thread of the thread group is assigned to a different execution unit within the GPGPU core 262. Instructions can access any of the local, shared, or global address spaces by specifying an address within the unified address space. The address mapping unit 256 can be used to convert addresses in the unified address space into distinct memory addresses that can be accessed by the load / store unit 266.

[0077] The register file 258 provides a set of registers for the functional units of the graphics multiprocessor 324. The register file 258 provides temporary storage for operands for the data paths of the functional units (e.g., GPGPU core 262, load / store unit 266) connected to the graphics multiprocessor 324. In one embodiment, the register file 258 is divided between each of these functional units so that each functional unit is allocated a dedicated portion of the register file 258. In one embodiment, the register file 258 is divided between different warps executed by the graphics multiprocessor 324.

[0078] The GPGPU cores 262 may each include a floating point unit (FPU) and / or an integer arithmetic logic unit (ALU) that is used to execute instructions of the graphics multiprocessor 324. Depending on the embodiment, the GPGPU cores 262 may be similar in architecture, or may be different in architecture. For example and in one embodiment, the first portion of the GPGPU core 262 includes a single-precision FPU and an integer ALU, while the second portion of the GPGPU core includes a double-precision FPU. In one embodiment, the FPU may implement the IEEE 754-2008 standard for floating-point arithmetic, or may implement variable-precision floating-point arithmetic. The graphics multiprocessor 324 may additionally include one or more fixed-function or special-function units to perform specific functions (e.g., copy rectangles or pixel blending operations). In one embodiment, one or more of the GPGPU cores may also include fixed or special-function logic.

[0079] In one embodiment, GPGPU core 262 includes SIMD logic that can execute single instruction to multiple groups of data. In one embodiment, GPGPU core 262 can physically execute SIMD4, SIMD8 and SIMD16 instructions, and logically execute SIMD1, SIMD2 and SIMD32 instructions. SIMD instructions for GPGPU core can be generated by shader compiler at compile time, or can be automatically generated when executing a program written and compiled as single program multiple data (SPMD) or SIMT architecture. Multiple threads of a program configured for SIMT execution model can be executed via a single SIMD instruction. For example, in one embodiment, eight SIMT threads performing the same or similar operation can be executed in parallel via a single SIMD8 logic unit.

[0080] The memory and cache interconnect 268 is an interconnect network that connects each of the functional units of the graphics multiprocessor 234 to the register file 258 and to the shared memory 270. In one embodiment, the memory and cache interconnect 268 is a crossbar interconnect that allows the load / store unit 266 to implement load and store operations between the shared memory 270 and the register file 258. The register file 258 can operate at the same frequency as the GPGPU core 262, so that data transfer between the GPGPU core 262 and the register file 258 is very low latency. The shared memory 270 can be used to implement communication between threads executing on the functional units within the graphics multiprocessor 234. The cache memory 272 can be used, for example, as a data cache to cache texture data communicated between the functional units and the texture unit 236. The shared memory 270 can also be used as a program-managed cache. Threads executing on the GPGPU core 262 can programmatically store data in the shared memory in addition to the automatically cached data stored in the cache memory 272.

[0081] FIG. 3A to FIG. 3B Additional graphics multiprocessors are shown according to embodiments. The graphics multiprocessors 325, 350 shown are Figure 2C The illustrated graphics multiprocessors 325, 350 may be configured as streaming multiprocessors (SMs) capable of executing a large number of execution threads simultaneously.

[0082] Figure 3A A graphics multiprocessor 325 is shown according to an additional embodiment. The graphics multiprocessor 325 is Figure 2DThe graphics multiprocessor 234 includes multiple additional instances of execution resource units. For example, the graphics multiprocessor 325 may include multiple instances of instruction units 332A to 332B, register files 334A-334B, and texture units 344A-344B. The graphics multiprocessor 325 also includes multiple groups of graphics or compute execution units (e.g., GPGPU cores 336A to 336B, GPGPU cores 337A to 337B, GPGPU cores 338A to 338B) and multiple groups of load / store units 340A to 340B. In one embodiment, the execution resource units have a common instruction cache 330, texture and / or data cache memory 342, and shared memory 346.

[0083] The various components may communicate via the interconnect structure 327. In one embodiment, the interconnect structure 327 includes one or more crossbar switches to enable communication between the various components of the graphics multiprocessor 325. In one embodiment, the interconnect structure 327 is a separate high-speed network fabric layer on which each component of the graphics multiprocessor 325 is stacked. The components of the graphics multiprocessor 325 communicate with remote components via the interconnect structure 327. For example, the GPGPU cores 336A-336B, 337A-337B, and 338A-338B may each communicate with the shared memory 346 via the interconnect structure 327. The interconnect structure 327 may arbitrate communications within the graphics multiprocessor 325 to ensure fair bandwidth allocation between components.

[0084] Figure 3B FIG. 3 shows a graphics multiprocessor 350 according to an additional embodiment. The graphics processor includes multiple sets of execution resources 356A to 356D, wherein each set of execution resources includes multiple instruction units, register files, GPGPU cores, and load storage units, such as Figure 2D and Figure 3A Execution resources 356A-356D may work in concert with texture units 360A-360D to perform texture operations while sharing instruction cache 354 and shared memory 362. In one embodiment, execution resources 356A-356D may share multiple instances of instruction cache 354 and shared memory 362 as well as texture and / or data cache memories 358A-358B. The various components may be communicated to one another via a communication protocol similar to Figure 3A The interconnect structure 327 and the interconnect structure 352 communicate with each other.

[0085] Those skilled in the art will understand that Figure 1 , FIG. 2A to FIG. 2D as well as FIG. 3A to FIG. 3BThe architecture described in is illustrative and non-limiting with respect to the scope of the present embodiments. Therefore, without departing from the scope of the embodiments described herein, the techniques described herein may be implemented on any properly configured processing unit, including but not limited to one or more mobile application processors, one or more desktop or server central processing units (CPUs) (including multi-core CPUs), one or more parallel processing units (e.g., parallel processing unit 202 of FIG. 2 ), and one or more graphics processors or special processing units.

[0086] In some embodiments, a parallel processor or GPGPU as described herein is communicatively coupled to a host / processor core to accelerate graphics operations, machine learning operations, pattern analysis operations, and various general-purpose GPU (GPGPU) functions. The GPU may be communicatively coupled to the host processor / core via a bus or other interconnect (e.g., a high-speed interconnect such as PCIe or NVLink). In other embodiments, the GPU may be integrated on the same package or chip as these cores and communicatively coupled to these cores via an internal processor bus / interconnect (i.e., inside the package or chip). Regardless of the manner in which the GPU is connected, the processor core can assign work to the GPU in the form of a sequence of commands / instructions contained in a work descriptor. The GPU then uses dedicated circuits / logic to efficiently process these commands / instructions.

[0087] Technologies for GPU to host processor interconnect

[0088] Figure 4A An exemplary architecture is shown in which multiple GPUs 410 to 413 are communicatively coupled to multiple multi-core processors 405 to 406 via high-speed links 440 to 443 (e.g., buses, point-to-point interconnects, etc.). In one embodiment, the high-speed links 440 to 443 support 4GB / s, 30GB / s, 80GB / s, or higher communication throughput, depending on the implementation. Various interconnect protocols may be used, including but not limited to PCIe 4.0 or 5.0 and NVLink 2.0. However, the underlying principles of the invention are not limited to any particular communication protocol or throughput.

[0089] Additionally, in one embodiment two or more of the GPUs 410 to 413 are interconnected via high-speed links 444 to 445, which may be implemented using the same or different protocols / links as used for high-speed links 440 to 443. Similarly, two or more of the multi-core processors 405 to 406 may be connected via high-speed link 433, which may be a symmetric multiprocessor (SMP) bus operating at 20 GB / s, 30 GB / s, 120 GB / s, or higher. Alternatively, Figure 4AAll communications between the various system components shown in can be accomplished using the same protocols / links (eg, via a common interconnect structure). However, as mentioned, the underlying principles of the invention are not limited to any particular type of interconnect technology.

[0090] In one embodiment, each multi-core processor 405-406 is communicatively coupled to processor memory 401-402 via memory interconnects 430-431, respectively, and each GPU 410-413 is communicatively coupled to GPU memory 420-423 via GPU memory interconnects 450-453, respectively. The memory interconnects 430-431 and 450-453 may utilize the same or different memory access technologies. By way of example and not limitation, the processor memory 401-402 and the GPU memory 420-423 may be volatile memory, such as dynamic random access memory (DRAM) (including stacked DRAM), graphics DDR SDRAM (GDDR) (e.g., GDDR5, GDDR6), or high bandwidth memory (HBM), and / or may be non-volatile memory, such as 3D XPoint or nano random access memory. In one embodiment, a portion of the memory may be volatile memory and another portion may be non-volatile memory (e.g., using a two-level memory (2LM) hierarchy).

[0091] As described below, although the various processors 405-406 and GPUs 410-413 may be physically coupled to specific memories 401-402, 420-423, respectively, a unified memory architecture may be implemented in which the same virtual system address space (also referred to as an "effective address" space) is distributed among all of the various physical memories. For example, the processor memories 401-402 may each include 64GB of system memory address space, and the GPU memories 420-423 may each include 32GB of system memory address space (yielding a total of 256GB of addressable memory in this example).

[0092] Figure 4B Additional details are shown for the interconnection between the multi-core processor 407 and the graphics acceleration module 446 according to one embodiment. The graphics acceleration module 446 may include one or more GPU chips integrated on a line card that is coupled to the processor 407 via the high-speed link 440. Alternatively, the graphics acceleration module 446 may be integrated on the same package or chip as the processor 407.

[0093] The processor 407 shown includes multiple cores 460A to 460D, each core having a translation lookaside buffer 461A to 461D and one or more caches 462A to 462D. These cores may include various other components for executing instructions and processing data, which are not shown to avoid obscuring the basic principles of the present invention (e.g., instruction acquisition units, branch prediction units, decoders, execution units, reorder buffers, etc.). Caches 462A to 462D may include level 1 (L1) and level 2 (L2) caches. In addition, one or more shared caches 426 may be included in the cache hierarchy and shared by multiple groups of cores 460A to 460D. For example, one embodiment of the processor 407 includes 24 cores, each core having its own L1 cache, 12 shared L2 caches, and 12 shared L3 caches. In this embodiment, one of the L2 and L3 caches is shared by two adjacent cores. The processor 407 and the graphics accelerator integrated module 446 are connected to the system memory 441 , which may include the processor memories 401 to 402 .

[0094] The coherence of data and instructions stored in the various caches 462A-462D, 456, and the system memory 441 is maintained via inter-core communications over the coherence bus 464. For example, each cache may have cache coherence logic / circuitry associated therewith to communicate via the coherence bus 464 in response to a detected read or write to a particular cache line. In one implementation, a cache snooping protocol is implemented via the coherence bus 464 to snoop cache accesses. Cache snooping / coherence techniques are well understood by those skilled in the art and will not be described in detail herein to avoid obscuring the underlying principles of the present invention.

[0095] In one embodiment, the proxy circuit 425 communicatively couples the graphics acceleration module 446 to the coherence bus 464, thereby allowing the graphics acceleration module 446 to participate in the cache coherence protocol as a peer of the core. Specifically, the interface 435 provides connectivity to the proxy circuit 425 via a high-speed link 440 (e.g., a PCIe bus, NVLink, etc.), and the interface 437 connects the graphics acceleration module 446 to the link 440.

[0096] In one implementation, the accelerator integrated circuit 436 provides cache management, memory access, context management, and interrupt management services on behalf of the multiple graphics processing engines 431, 432, N of the graphics acceleration module 446. The graphics processing engines 431, 432, N may each include a separate graphics processing unit (GPU). Alternatively, the graphics processing engines 431, 432, N may include different types of graphics processing engines within the GPU, such as a graphics execution unit, a media processing engine (e.g., a video encoder / decoder), a sampler, and a bit block transfer (blit) engine. In other words, the graphics acceleration module may be a GPU with multiple graphics processing engines 431 to 432, N, or the graphics processing engines 431 to 432, N may be individual GPUs integrated on a common package, line card, or chip.

[0097] In one embodiment, the accelerator integrated circuit 436 includes a memory management unit (MMU) 439 for performing various memory management functions, such as virtual to physical memory translation (also known as effective to real memory translation) and memory access protocols for accessing the system memory 441. The MMU 439 may also include a translation lookaside buffer (TLB) (not shown) for virtual / effective cache to physical / real address translation. In one implementation, the cache 438 stores commands and data for effective access by the graphics processing engines 431 to 432, N. In one embodiment, the data stored in the cache 438 and the graphics memory 433 to 434, N is kept consistent with the core caches 462A to 462D, 456 and the system memory 411. As mentioned, this may be accomplished via proxy circuitry 425, which participates in cache coherence mechanisms on behalf of cache 438 and memories 433 to 434, N (e.g., sending updates related to modifications / accesses to cache lines on processor caches 462A to 462D, 456 to and receiving updates from cache 438).

[0098] A set of registers 445 stores context data for threads executed by the graphics processing engines 431 to 432, N, and context management circuitry 448 manages thread contexts. For example, context management circuitry 448 may perform save and restore operations during context switching to save and restore contexts of various threads (e.g., where a first thread is saved and a second thread is stored so that the second thread can be executed by the graphics processing engine). For example, upon context switching, context management circuitry 448 may store current register values ​​to a designated area in memory (e.g., identified by a context pointer). It may then restore these register values ​​upon returning to the context. In one embodiment, interrupt management circuitry 447 receives and processes interrupts received from system devices.

[0099] In one implementation, virtual / effective addresses from the graphics processing engine 431 are converted to real / physical addresses in the system memory 411 by the MMU 439. One embodiment of the accelerator integrated circuit 436 supports multiple (e.g., 4, 8, 16) graphics accelerator modules 446 and / or other accelerator devices. The graphics accelerator module 446 may be dedicated to a single application executing on the processor 407, or may be shared between multiple applications. In one embodiment, a virtualized graphics execution environment is presented in which multiple applications or virtual machines (VMs) share the resources of the graphics processing engines 431 to 432, N. These resources may be subdivided into "slices" that are allocated to the different VMs and / or applications based on the processing requirements and priorities associated with the different VMs and / or applications.

[0100] Thus, the accelerator integrated circuit acts as a bridge to the system of graphics acceleration module 446 and provides address translation and system memory cache services. In addition, the accelerator integrated circuit 436 can provide virtualization facilities for the host processor to manage virtualization, interrupts and memory management of the graphics processing engine.

[0101] Since the hardware resources of the graphics processing engines 431-432, N are explicitly mapped to the real address space seen by the host processor 407, any host processor can directly address these resources using effective address values. In one embodiment, one function of the accelerator integrated circuit 436 is to physically separate the graphics processing engines 431-432, N so that they appear to the system as independent units.

[0102] As mentioned, in the illustrated embodiment, one or more graphics memories 433-434, M are respectively coupled to each of the graphics processing engines 431-432, N. The graphics memories 433-434, M store instructions and data processed by each of the graphics processing engines 431-432, N. The graphics memories 433-434, M may be volatile memory, such as DRAM (including stacked DRAM), GDDR memory (e.g., GDDR5, GDDR6), or HBM, and / or may be non-volatile memory, such as 3D XPoint or Nano-Random Access Memory (Nano-Ram).

[0103] In one embodiment, to reduce data traffic on link 440, biasing techniques are used to ensure that the data stored in graphics memory 433-434, M is data that will be used most frequently by graphics processing engines 431-432, N and preferably not used (at least not frequently) by cores 460A-460D. Similarly, the biasing mechanism attempts to keep data needed by cores (and preferably not by graphics processing engines 431-432, N) within the caches 462A-462D, 456 of these cores and system memory 411.

[0104] Figure 4C Another embodiment is shown in which an accelerator integrated circuit 436 is integrated within the processor 407. In this embodiment, the graphics processing engines 431-432, N communicate directly to the accelerator integrated circuit 436 via the interface 437 and the interface 435 (again, these interfaces can utilize any form of bus or interface protocol) through the high-speed link 440. The accelerator integrated circuit 436 can perform operations related to Figure 4B The same operations are described, but at potentially higher throughput given their close proximity to the coherency bus 462 and caches 462A-462D, 426.

[0105] One embodiment supports different programming models, including a dedicated process programming model (without graphics acceleration module virtualization) and a shared programming model (with virtualization). The latter may include a programming model controlled by accelerator integrated circuit 436 and a programming model controlled by graphics acceleration module 446.

[0106] In one embodiment of a dedicated process model, the graphics processing engines 431 to 432, N are dedicated to a single application or process under a single operating system. A single application can funnel other application requests to the graphics engines 431 to 432, N, thereby providing virtualization within a VM / partition.

[0107] In a dedicated process programming model, graphics processing engines 431 to 432, N can be shared by multiple VM / application partitions. The shared model requires a hypervisor to virtualize graphics processing engines 431 to 432, N to allow access by each operating system. For a single partition system without a hypervisor, graphics processing engines 431 to 432, N are owned by the operating system. In both cases, the operating system can virtualize graphics processing engines 431 to 432, N to provide access to each process or application.

[0108] For the shared programming model, the graphics acceleration module 446 or the individual graphics processing engines 431 to 432, N use the process handle to select a process element. In one embodiment, the process elements are stored in the system memory 411 and can be addressed using the effective address to real address translation techniques described herein. The process handle can be an implementation-specific value provided to the host process when registering its context with the graphics processing engine 431 to 432, N (that is, calling the system software to add the process element to the process element linked list). The lower 16 bits of the process handle can be the offset of the process element within the process element linked list.

[0109] Figure 4D An exemplary accelerator integrated slice 490 is shown. As used herein, a "slice" includes a specified portion of the processing resources of an accelerator integrated circuit 436. An application effective address space 482 within the system memory 411 stores process elements 483. In one embodiment, the process elements 483 are stored in response to a GPU call 481 from an application 480 executed on a processor 407. The process element 483 contains the process state of the corresponding application 480. The work descriptor (WD) 484 contained in the process element 483 can be a single job requested by the application, or can contain a pointer to a job queue. In the latter case, WD484 is a pointer to a job request queue in the address space 482 of the application.

[0110] Graphics acceleration module 446 and / or individual graphics processing engines 431-432, N may be shared by all processes or a subset of processes in the system. Embodiments of the present invention include infrastructure for setting process state and sending WD 484 to graphics acceleration module 446 to start a job in a virtualized environment.

[0111] In one implementation, the dedicated process programming model is implementation specific. In this model, a single process owns the graphics acceleration module 446 or individual graphics processing engine 431. Since the graphics acceleration module 446 is owned by a single process, when the graphics acceleration module 446 is assigned, the hypervisor initializes the accelerator integrated circuit 436 for the owning partition and the operating system initializes the accelerator integrated circuit 436 for the owning process.

[0112] In operation, the WD acquisition unit 491 in the accelerator integrated slice 490 acquires the next WD 484, which includes an indication of work to be completed by one of the graphics processing engines of the graphics acceleration module 446. Data from the WD 484 may be stored in registers 445 and used by the MMU 439, interrupt management circuit 447, and / or context management circuit 446 as shown. For example, one embodiment of the MMU 439 includes a segment / page walk circuit for accessing a segment / page table 486 within the OS virtual address space 485. The interrupt management circuit 447 may process an interrupt event 492 received from the graphics acceleration module 446. When performing graphics operations, the effective address 493 generated by the graphics processing engine 431 to 432, N is converted to a real address by the MMU 439.

[0113] In one embodiment, a set of identical registers 445 are replicated for each graphics processing engine 431 to 432, N, and / or graphics acceleration module 446, and these registers may be initialized by a hypervisor or operating system. Each of these replicated registers may be included in an accelerator integrated slice 490. Exemplary registers that may be initialized by a hypervisor are shown in Table 1.

[0114] Table 1 - Registers initialized by the hypervisor

[0115] 1 Slice Control Register 2 Real address (RA) dispatched process area pointer 3 Authority Mask Override Register 4 Interrupt vector table entry offset 5 Interrupt Vector Table Entry Limits 6 Status Register 7 Logical Partition ID 8 Real Address (RA) Hypervisor Accelerator Utilizing Record Pointers 9 Storage Description Register

[0116] Example registers that may be initialized by the operating system are shown in Table 2.

[0117] Table 2 - Registers initialized by the operating system

[0118] 1 Process and thread identities 2 Effective Address (EA) context save / restore pointer 3 Virtual Address (VA) Accelerator Utilizes Record Pointers 4 Virtual Address (VA) Segment Table Pointer 5 Permission Mask 6 Job Descriptor

[0119] In one embodiment, each WD 484 is specific to a particular graphics acceleration module 446 and / or graphics processing engine 431-432, N. It contains all the information needed by the graphics processing engine 431-432, N to complete its work, or it may be a pointer to a memory location where the application has set up a command queue for work to be done.

[0120] Figure 4E Additional details of one embodiment of a sharing model are presented. This embodiment includes a hypervisor real address space 498 in which a process element list 499 is stored. The hypervisor real address space 498 is accessible via a hypervisor 496 that virtualizes a graphics acceleration module engine for an operating system 495.

[0121] The shared programming model allows all processes or subsets of processes from all partitions or subsets of partitions in the system to use the graphics acceleration module 446. There are two programming models where the graphics acceleration module 446 is shared by multiple processes and partitions: time-sliced ​​shared and graphics directed shared.

[0122] In this model, the hypervisor 496 owns the graphics acceleration module 446 and makes its functionality available to all operating systems 495. In order for the graphics acceleration module 446 to support virtualization by the hypervisor 496, the graphics acceleration module 446 may comply with the following requirements: 1) The application's job requests must be autonomous (i.e., no state needs to be maintained between jobs), or the graphics acceleration module 446 must provide a context save and restore mechanism. 2) The application's job requests must be guaranteed to be completed within a specified amount of time by the graphics acceleration module 446 (including any transition failures), or the graphics acceleration module 446 provides the ability to preempt the processing of a job. 3) When operating in a directed-sharing programming model, the graphics acceleration module 446 must be guaranteed fairness between processes.

[0123] In one embodiment, for the shared model, the application 480 is required to use the graphics acceleration module 446 type, work descriptor (WD), permission mask register (AMR) value and context save / restore region pointer (CSRP) to make an operating system 495 system call. The graphics acceleration module 446 type describes the target acceleration function for the system call. The graphics acceleration module 446 type can be a system-specific value. The WD is formatted specifically for the graphics acceleration module 446 and can be in the form of a graphics acceleration module 446 command, an effective address pointer to a user-defined structure, an effective address pointer to a command queue, or any other data structure for describing the work to be completed by the graphics acceleration module 446. In one embodiment, the AMR value is the AMR state to be used for the current process. The value passed to the operating system is similar to the application of setting the AMR. If the accelerator integrated circuit 436 and the graphics acceleration module 446 implementation do not support the user permission mask override register (UAMOR), the operating system can apply the current UAMOR value to the AMR value and then pass the AMR in the hypervisor call. Optionally, the hypervisor 496 may apply the current permission mask overwrite register (AMOR) value before placing the AMR into the process element 483. In one embodiment, the CSRP is one of the registers 445 that contains the effective address of an area in the application's address space 482 for the graphics acceleration module 446 to save and restore context state. This pointer is optional if state does not need to be saved between jobs or when a job is preempted. The context save / restore area may be pinned system memory.

[0124] Upon receiving the system call, the operating system 495 may verify that the application 480 has been registered and has been given permission to use the graphics acceleration module 446. The operating system 495 then calls the hypervisor 496 using the information shown in Table 3.

[0125] Table 3 – OS to Hypervisor call parameters

[0126] 1 Work Descriptor (WD) 2 The permission mask register (AMR) value (potentially masked) 3 Effective Address (EA) Context Save / Restore Region Pointer (CSRP) 4 Process ID (PID) and optional thread ID (TID) 5 Virtual Address (VA) Accelerator Utilization Record Pointer (AURP) 6 Virtual address of the storage segment table pointer (SSTP) 7 Logical Interrupt Service Number (LISN)

[0127] Upon receiving the hypervisor call, the hypervisor 496 verifies that the operating system 495 has been registered and has been given permission to use the graphics acceleration module 446. The hypervisor 496 then places the process element 483 into a linked list of process elements of the corresponding graphics acceleration module 446 type. The process element may include the information shown in Table 4.

[0128] Table 4 - Process element information

[0129] 1 Work Descriptor (WD) 2 The permission mask register (AMR) value (potentially masked) 3 Effective Address (EA) Context Save / Restore Region Pointer (CSRP) 4 Process ID (PID) and optional thread ID (TID) 5 Virtual Address (VA) Accelerator Utilization Record Pointer (AURP) 6 Virtual address of the storage segment table pointer (SSTP) 7 Logical Interrupt Service Number (LISN) 8 Interrupt vector table derived from hypervisor call parameters 9 Status Register (SR) Value 10 Logical Partition ID (LPID) 11 Real Address (RA) Hypervisor Accelerator Utilizing Record Pointers 12 Memory Descriptor Register (SDR)

[0130] In one embodiment, the hypervisor initializes the plurality of accelerator integrated slice 490 registers 445 .

[0131] like Figure 4F As shown in , one embodiment of the present invention employs a unified memory addressable via a common virtual memory address space for accessing physical processor memories 401-402 and GPU memories 420-423. In this implementation, operations executed on GPUs 410-413 utilize the same virtual / effective memory address space to access processor memories 401-402 and vice versa, thereby simplifying programmability. In one embodiment, a first portion of the virtual / effective address space is allocated to processor memory 401, a second portion is allocated to second processor memory 402, a third portion is allocated to GPU memory 420, and so on. This allows the entire virtual / effective memory space (sometimes referred to as the effective address space) to be distributed across each of processor memories 401-402 and GPU memories 420-423, thereby allowing any processor or GPU to access any physical memory using a virtual address mapped to the memory.

[0132] In one embodiment, bias / coherency management circuits 494A-494E within one or more of MMUs 439A-439E ensure cache coherency between caches of a host processor (e.g., 405) and GPUs 410-413 and implement biasing techniques that indicate physical memory where certain types of data should be stored. Figure 4F 4. Multiple instances of bias / consistency management circuits 494A-494E are shown in , but bias / consistency circuits may be implemented within an MMU of one or more host processors 405 and / or within an accelerator integrated circuit 436.

[0133] One embodiment allows GPU-attached memory 420 to 423 to be mapped as part of system memory and accessed using shared virtual memory (SVM) technology, but without the typical performance drawbacks associated with full system cache coherence. The ability of GPU-attached memory 420 to 423 to be accessed as system memory without heavy cache coherence overhead provides a beneficial operating environment for GPU offloading. This arrangement allows host processor 405 software to set operands and access calculation results without the overhead of traditional I / O DMA data copying. Such traditional copying involves driver calls, interrupts, and memory-mapped I / O (MMIO) accesses, which are all inefficient relative to simple memory accesses. At the same time, the ability to access GPU-attached memory 420 to 423 without cache coherence overhead can be critical to the execution time of the offloaded calculation. In the case of substantial streaming write memory traffic, for example, cache coherence overhead can significantly reduce the effective write bandwidth seen by GPUs 410 to 413. The efficiency of operand setup, the efficiency of result access, and the efficiency of GPU calculation all play a role in determining the effectiveness of GPU offloading.

[0134] In one implementation, the selection between GPU bias and host processor bias is driven by a bias tracker data structure. A bias table may be used, for example, which may be a page granular structure including 1 or 2 bits per GPU attached memory page (i.e., controlled at the granularity of a memory page). The bias table may be implemented using stolen memory ranges of one or more GPU attached memories 420 to 423, with or without a bias cache in GPUs 410 to 413 (e.g., to cache frequently used / recently used entries of the bias table). Alternatively, the entire bias table may be maintained within the GPU.

[0135] In one implementation, the bias table entry associated with each access to GPU attached memory 420 to 423 is accessed before actually accessing the GPU memory, resulting in the following operations. First, local requests from GPUs 410 to 413 that find their pages in the GPU bias (these local requests find their pages in the GPU bias) are forwarded directly to the corresponding GPU memory 420 to 423. Local requests from the GPU (these local requests find their pages in the host bias) are forwarded to the processor 405 (e.g., via a high-speed link as discussed above). In one embodiment, the request from the processor 405 to find the requested page in the host processor bias completes a request similar to a normal memory read. Alternatively, the request for the GPU bias page can be forwarded to the GPU 410 to 413. Then, if the GPU is not currently using the page, it can transfer the page to the host processor bias.

[0136] The bias state of a page may be changed by a software-based mechanism, a hardware-assisted software-based mechanism, or, for a limited set of circumstances, a purely hardware-based mechanism.

[0137] One mechanism for changing the bias state employs an API call (e.g., OpenCL) which in turn calls the GPU's device driver which in turn sends a message (or queues a command descriptor) to the GPU instructing it to change the bias state and perform a cache flushing operation in the host for some transitions. The cache flushing operation is required for transitions from host processor 405 bias to GPU bias, but not for the reverse transition.

[0138] In one embodiment, cache coherency is maintained by temporarily rendering GPU biased pages that are not cacheable by host processor 405. To access these pages, processor 405 may request access from GPU 410, which may or may not be granted immediately, depending on the implementation. Therefore, to reduce communication between processor 405 and GPU 410, it is advantageous to ensure that GPU biased pages are those pages that are needed by the GPU but not by host processor 405 (and vice versa).

[0139] Graphics processing pipeline

[0140] Figure 5 A graphics processing pipeline 500 according to an embodiment is shown. In one embodiment, a graphics processor may implement the illustrated graphics processing pipeline 500. The graphics processor may be included in a parallel processing subsystem as described herein, such as the parallel processing subsystem 200 of FIG. 2 , which in one embodiment is Figure 1 2 . Various parallel processing systems may implement the graphics processing pipeline 500 via one or more instances of a parallel processing unit (e.g., parallel processing unit 202 of FIG. 2 ) as described herein. For example, a shader unit (e.g., graphics multiprocessor 234 of FIG. 3 ) may be configured to perform the functions of one or more of a vertex processing unit 504, a tessellation control processing unit 508, a tessellation evaluation processing unit 512, a geometry processing unit 516, and a fragment / pixel processing unit 524. The functions of the data assembler 502, the primitive assemblers 506, 514, 518, the tessellation unit 510, the rasterizer 522, and the raster operation unit 526 may also be performed by other processing engines within a processing cluster (e.g., processing cluster 214 of FIG. 3 ) and corresponding partition units (e.g., partition units 220A to 220N of FIG. 2 ). The graphics processing pipeline 500 may also be implemented using dedicated processing units for one or more functions. In one embodiment, one or more portions of graphics processing pipeline 500 may be executed by parallel processing logic within a general purpose processor (e.g., a CPU). In one embodiment, one or more portions of graphics processing pipeline 500 may access on-chip memory (e.g., such as parallel processor memory 222 in FIG. 2 ) via memory interface 528, which may be an example of memory interface 218 in FIG. 2 .

[0141] In one embodiment, data assembler 502 is a processing unit that collects vertex data for surfaces and primitives. Data assembler 502 then outputs vertex data including vertex attributes to vertex processing unit 504. Vertex processing unit 504 is a programmable execution unit that executes vertex shader programs to illuminate and transform vertex data as specified by the vertex shader programs. Vertex processing unit 504 reads data stored in cache, local or system memory for use in processing vertex data, and vertex processing unit 504 can be programmed to transform vertex data from an object-based coordinate representation to a world space coordinate space or a normalized device coordinate space.

[0142] A first instance of primitive assembler 506 receives vertex attributes from vertex processing unit 504. Primitive assembler 506 reads the stored vertex attributes as needed and builds graphics primitives for processing by tessellation control processing unit 508. Graphics primitives include triangles, line segments, points, patches, etc., which are supported by various graphics processing application programming interfaces (APIs).

[0143] The tessellation control processing unit 508 treats the input vertices as control points for the geometric patch. The control points are converted from the input representation from the patch (e.g., the basis of the patch) to a representation suitable for use in the surface evaluation by the tessellation evaluation processing unit 512. The tessellation control processing unit 508 can also calculate the tessellation factors for the edges of the geometric patch. The tessellation factors are applied to a single edge and the view-dependent detail level associated with the edge is quantized. The tessellation unit 510 is configured to receive the tessellation factors for the edges of the patch and tessellate the patch into a plurality of geometric primitives such as lines, triangles, or quadrilateral primitives, which are transmitted to the tessellation evaluation processing unit 512. The tessellation evaluation processing unit 512 operates on the parameterized coordinates of the subdivided patch to generate a surface representation and vertex attributes for each vertex associated with the geometric primitive.

[0144] A second instance of primitive assembler 514 receives vertex attributes from tessellation evaluation processing unit 512, reads stored vertex attributes as needed, and builds graphics primitives for processing by geometry processing unit 516. Geometry processing unit 516 is a programmable execution unit that executes geometry shader programs to transform graphics primitives received from primitive assembler 514 as specified by the geometry shader programs. In one embodiment, geometry processing unit 516 is programmed to subdivide a graphics primitive into one or more new graphics primitives and to compute parameters for rasterizing the new graphics primitives.

[0145] In some embodiments, the geometry processing unit 516 may add or delete elements in the geometry stream. The geometry processing unit 516 outputs parameters and vertices specifying new graphics primitives to the primitive assembler 518. The primitive assembler 518 receives the parameters and vertices from the geometry processing unit 516 and constructs graphics primitives for processing by the viewport scaling, picking, and clipping unit 520. The geometry processing unit 516 reads data stored in the parallel processor memory or the system memory for use in processing the geometry data. The viewport scaling, picking, and clipping unit 520 performs clipping, picking, and viewport scaling, and outputs the processed graphics primitives to the rasterizer 522.

[0146] The rasterizer 522 can perform depth sorting and other depth-based optimizations. The rasterizer 522 also performs scan conversion on new graphics primitives to generate fragments, and outputs those fragments and associated coverage data to the fragment / pixel processing unit 524. The fragment / pixel processing unit 524 is a programmable execution unit configured to execute a fragment shader program or a pixel shader program. The fragment / pixel processing unit 524 transforms fragments or pixels received from the rasterizer 522 as specified by the fragment or pixel shader program. For example, the fragment / pixel processing unit 524 can be programmed to perform operations to generate shaded fragments or pixels output to the raster operation unit 526, including but not limited to texture mapping, shading, blending, texture correction, and perspective correction. The fragment / pixel processing unit 524 can read data stored in a parallel processor memory or system memory for use in processing fragment data. The fragment or pixel shader program can be configured to shade with samples, pixels, tiles, or other granularity depending on the sampling rate configured for the processing unit.

[0147] Raster operations unit 526 is a processing unit that performs raster operations including, but not limited to, stenciling, z-testing, blending, etc., and outputs pixel data as processed graphics data for storage in graphics memory (e.g., parallel processor memory 222 and / or Figure 1 The raster operations unit 526 may be configured to compress the z or color data written to the memory and to decompress the z or color data read from the memory.

[0148] Collaborative Multi-User VR Example

[0149] Now turn to Fig. 6A, an embodiment of the electronic processing system 600 may include: an application processor 601; a permanent storage medium 602, communicatively coupled to the application processor 601; and a graphics subsystem 603, communicatively coupled to the application processor 601. The system 600 may further include: a sensing engine 604, communicatively coupled to the graphics subsystem 603 to provide sensed information; a focus engine 605, communicatively coupled to the sensing engine 604 and the graphics subsystem 603 to provide focus information; a motion engine 606, communicatively coupled to the sensing engine 604, the focus engine 605, and the graphics subsystem 603 to provide motion information; and a collaboration engine 607, communicatively coupled to one or more of the motion engine 606, the focus engine 605, and the sensing engine 604 to identify shared graphic components between two or more users in an environment and share the shared graphic components with the two or more users in the environment.

[0150] The embodiments of each of the above-mentioned application processor 601, permanent storage medium 602, graphics subsystem 603, sensing engine 604, focus engine 605, motion engine 606, collaboration engine 607, and other system components can be implemented in hardware, software, or any appropriate combination thereof. For example, the hardware implementation may include configurable logic, such as programmable logic array (PLA), FPGA, complex programmable logic device (CPLD), or fixed function logic hardware using circuit technology such as ASIC, complementary metal oxide semiconductor (CMOS) or transistor-transistor logic (TTL) technology, or any combination thereof. Alternatively or additionally, these components can be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as random access memory (RAM), read-only memory (ROM), programmable ROM (PROM), firmware, flash memory, etc. For example, the computer program code for performing the operations of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages.

[0151] For example, system 600 may include similar components and / or features as system 100, further configured with a collaboration engine as described herein. Additionally or alternatively, graphics subsystem 603 may include similar components and / or features as parallel processor 200, further configured with a collaboration engine as described herein. System 600 may also be adapted to work with a stereo head mounted system, such as, for example, in combination with Figures 11 to 15 The system described.

[0152] Sensing Engine Example

[0153] Now turn to Figure 6B The sensing engine 612 may obtain information from sensors, content, services, and / or other sources to provide sensed information. The sensed information may include, for example, image information, audio information, motion information, depth information, temperature information, biometric information, GPU information, etc. At a high level, some embodiments may use the sensed information to reduce the workload of a user's graphics system or enhance the performance of the system.

[0154] For example, the sensing engine may include a sensor hub that is communicatively coupled to a two-dimensional (2D) camera, a three-dimensional (3D) camera, a depth camera, a gyroscope, an accelerometer, an inertial measurement unit (IMU), a positioning service, a microphone, a proximity sensor, a thermometer, a biometric sensor, etc., and / or a combination of multiple sources that provide information to the focus engine and / or motion engine. The sensor hub may be distributed across multiple devices. Information from the sensor hub may include or be combined with input data (e.g., touch data) from a user device.

[0155] For example, the user's (multiple) devices may include one or more 2D cameras, 3D cameras, and / or depth cameras. The user's (multiple) devices may also include gyroscopes, accelerometers, IMUs, location services, thermometers, biometric sensors, etc. For example, a user may carry a smart phone (e.g., in the user's pocket) and / or may wear a wearable device (e.g., such as a smart watch, an activity monitor, and / or a health tracker). The user's (multiple) devices may also include a microphone that can be used to detect whether the user is talking, making a phone call, talking to another nearby person, etc. The sensor hub may include some or all of the user's various devices that can collect information related to the user's actions or activities (e.g., including an I / O interface of a user device that can collect keyboard / mouse / touch activities). The sensor hub may obtain information directly from the collection device of the user's device (e.g., wired or wirelessly), or the sensor hub may be able to integrate information from the device according to a server or service (e.g., information that the sensor hub can download can be uploaded from a health tracker to a cloud service).

[0156] Focus Engine Example

[0157] Now turn to Figure 6C, the focus engine 614 can obtain information from the sensing engine and / or the motion engine and other sources to provide focus information. The focus information may include, for example, focus, focus area, eye position, eye movement, pupil size, pupil dilation, depth of focus (DOF), content focus, content focus object, content focus area, etc. The focus information may also include previous focus information, determined future focus information, and / or predicted focus information (e.g., predicted focus, predicted focus area, predicted eye position, predicted eye movement, predicted pupil size, predicted pupil dilation, predicted DOF, determined future content focus, determined future content focus object, determined future content focus area, predicted content focus, predicted content focus object, predicted content focus area, etc.).

[0158] At a high level, some embodiments may use focus information to reduce the workload of a user's graphics system or enhance the performance of the system based on: 1) assuming where the user is looking, 2) determining where the user is looking, 3) where the application wants the user to look, and / or 4) predicting where the user will look in the future. Some focus cues may be stronger in the focus area where the user is looking. If the user is looking straight ahead, they may see things in sharp focus. For scenes or objects towards the periphery, the user may notice motion but not details in sharp focus.

[0159] For example, if the sensed information or processing capabilities of the graphics system are limited (e.g., the attached head-mounted display (HMD) or host cannot provide or use the information), the focus information can be static and / or based on assumptions (e.g., assuming that the user is looking at the center of the screen with a fixed eye position, DOF, etc.). The focus information can also change dynamically based on information such as motion information (e.g., from a virtual reality (VR) headset), motion prediction information, content information (e.g., motion in a scene), etc. More preferably, a rich sensor group including eye tracking (sometimes also referred to as gaze tracking) can be used to identify the focus area and provide focus information to provide a better user experience. For example, some embodiments may include an eye tracker or obtain eye information from an eye tracker to track the user's eyes. The eye information may include eye position, eye movement, pupil size / dilation, depth of focus, etc. The eye tracker may capture an image of the user's eyes including the pupil. The user's focus and / or DOF may be determined, inferred, and / or estimated based on the eye position and pupil dilation. The user may undergo a calibration process, which may help the eye tracker provide more accurate focus and / or DOF information.

[0160] For example, when a user is wearing a VR headset, a camera can capture an image of the pupil, and the system can determine where the user is looking (e.g., focal area, depth, and / or direction). The camera can capture pupil dilation information, and the system can infer where the user's focal area is based on this information. For example, the human eye has a certain DOF, so that if a person focuses on something nearby, things in the distance may be blurry. The focus information may include the focus at the focus distance X and the DOF information of Δ(X), so the focus area may correspond to X+ / -delta[X] positioned around the user's focus. The size of the DOF may vary with the distance X (e.g., different Δ at different focus distances). For example, the user's DOF ​​may be calibrated and may vary in each direction (e.g., x, y, and z), so that the function delta[X] may not necessarily be spherical.

[0161] In some embodiments, the focus information may include content-based focus information. For example, in a 3D, VR, and / or augmented reality (AR) environment, depth and / or distance information (e.g., where the user is in the virtual environment, where the object is, and / or how far the object is from the user, etc.) may be provided from the application. Content-based focus information may also include points, objects, or areas in the content that the application wants the user to focus on, such as something more interesting that is happening that the application wants the user to pay attention to. The application may also be able to provide future content focus information because the application may know the motion information of the content and / or which objects / areas in the next frame or scene may be more interesting to the user (e.g., objects that are about to enter the scene from the edge of the screen).

[0162] Motion Engine Example

[0163] Now turn to Fig.6D , the motion engine 616 can obtain information from the sensing engine and / or the focus engine and other sources to provide motion information. The motion information may include, for example, head position, head speed, head acceleration, head movement direction, eye speed, eye acceleration, eye movement direction, object position, object speed, object acceleration, object movement direction, etc. The motion information may also include previous motion information, determined future motion information, and / or predicted motion information (e.g., predicted head speed, predicted head acceleration, predicted head position, predicted head movement direction, predicted eye speed, predicted eye acceleration, predicted eye movement direction, determined future content position, determined future content object speed, determined future content object acceleration, predicted object position, predicted object speed, predicted object acceleration, etc.).

[0164] At a high level, some embodiments may use motion information to reduce the workload of a user's graphics system or enhance the performance of the system based on: 1) the user moving their head, 2) the user moving their eyes, 3) the user moving their body, 4) the application wants the user to turn their head / eyes and / or body, and / or 4) predicting that the user will turn their head, eyes and / or body in the future. Some motion information can be easily determined from the sensed information. For example, head position, velocity, acceleration, direction of movement, etc. can be determined from an accelerometer. Eye movement information can be determined by tracking eye position information over time (e.g., if an eye tracker only provides eye position information).

[0165] Some motion information may be content-based. For example, in a game or real-time 3D content, an application may know how fast an object is moving and where it is moving. The application may provide information to a motion engine (e.g., through an API call). Future content-based object motion information for the next frame / scene may also be fed into the motion engine for decision making. Some content-based motion information may be determined by image processing or machine vision processing of the content.

[0166] For example, some embodiments of the machine vision system can analyze and / or perform feature / object recognition on images captured by a camera. For example, machine vision and / or image processing can identify and / or recognize objects in a scene (e.g., an edge belongs to the front of a chair). The machine vision system can also be configured to perform facial recognition, eye tracking, facial expression recognition, and / or gesture recognition, including gestures at the body level, gestures at the arm / leg level, gestures at the hand level, and / or gestures at the finger level. The machine vision system can be configured to classify the user's actions. In some embodiments, a suitably configured machine vision system can be able to determine whether the user is located at a computer, typing on a keyboard, using a mouse, using a trackpad, using a touch screen, using an HMD, using a VR system, sitting, standing, and / or otherwise taking some other action or activity.

[0167] For example, the motion engine can obtain camera data related to real objects in the scene, and can use this information to identify the motion and orientation of the real objects. The motion engine can obtain delay information from the graphics processor. The motion engine can then predict the orientation of the next frame of this real object. The amount of delay can be based on one or more of the time used to render the scene, the number of virtual objects in the scene, and the complexity of the scene. For example, the scene engine may include one or more cameras for capturing real scenes. For example, the one or more cameras may include one or more 2D cameras, 3D cameras, depth cameras, high-speed cameras, or other image acquisition devices. The real scene may include objects moving in the scene. The camera may be coupled to an image processor, which is used to process data from the camera to identify objects in the scene (e.g., including moving objects) and identify the motion of the object (e.g., including orientation information). The motion engine can determine the predicted motion information based on the motion of the tracking object, and predict the future position of the object based on the measured or estimated delay (e.g., from the acquisition time to the rendering time). According to some embodiments, optical flow technology and other real motion estimation technologies can be used to enhance various motion tracking and / or motion prediction technologies to determine the next position of the real object. For example, some embodiments may use extended common filtering and / or perspective processing (eg, from autonomous driving applications) to predict the motion of objects.

[0168] Collaboration Engine Example

[0169] Now turn to Fig. 6E , the collaboration engine 618 can obtain information from the sensing engine, the focus engine, the motion engine, the content, multiple users (e.g., HMD#1, HMD#2, to HMD#N), and / or other sources to provide shared information and optionally individual information (e.g., user-specific information). The shared information may include, for example, image information, audio information, motion information, depth information, temperature information, biometric information, GPU information, object space information, geometry information, primitive information, physical information, artificial intelligence (AI) information, etc. At a high level, some embodiments may use the shared information to reduce the workload of the user's (multiple) graphics system or enhance the performance of the system. The individual information (if provided) may include the same type of information specific to each user, and the user's system may merge the shared information with the specific information as needed.

[0170] Engine Overlap Example

[0171] Those skilled in the art will appreciate that aspects of the various engines described herein may overlap with other engines, and portions of each engine may be implemented or distributed throughout portions of an electronic processing system. For example, a focus engine may use motion information to provide a predicted future focus area, and a motion engine may use focus information to predict future motion. Eye movement information may come directly from a sensing engine, may be determined / predicted by a focus engine, and / or may be determined / predicted by a motion engine. The examples herein should be considered illustrative rather than limiting with respect to specific implementations.

[0172] Now turn to Fig. 6F , an embodiment of the graphics device 620 may include: a processor 621; a memory 622, communicatively coupled to the processor 621; and a collaboration engine 623, communicatively coupled to the processor for identifying shared graphics components between two or more users in an environment and sharing the shared graphics components with the two or more users in the environment.

[0173] Some embodiments of device 620 may include any number of additional modules for supporting collaborative graphics processing. For example, collaboration engine 623 may include one or more of centralized sharer 624, deep sharer 625, shared preprocessor 626, multi-port graphics subsystem 627, and decode sharer 628.

[0174] In some embodiments of the device 620, for example, the collaboration engine 623 may further include a centralized sharer 624 (e.g., as described in more detail below). For example, the centralized sharer may be configured to broadcast the shared graphics component to all of the two or more users and to individually distribute the individual graphics component to one of the two or more users. The centralized sharer 624 may be further configured to split the workload of the shared graphics component based on the target virtual reality device.

[0175] In some embodiments of the device 620, for example, the collaboration engine 623 may further include a depth sharer 625 (e.g., as described in more detail below). For example, the depth sharer 625 may be configured to collect depth information from a source independent of a first user of the two or more users and share the depth information with the first user. The depth sharer 625 may be further configured to collect visibility information from the independent source outside the field of view of the first user and share the visibility information with the first user.

[0176] In some embodiments of the device 620, for example, the collaboration engine 623 may further include a sharing preprocessor 626 (e.g., as described in more detail below). For example, the sharing preprocessor 626 may be configured to precompute information related to the shared graphics component and share the precomputed information with the two or more users. The precomputed information may include one or more of geometric information, primitive information, and physical information.

[0177] In some embodiments of device 620, for example, collaboration engine 623 may further include a multi-port graphics subsystem 627 (e.g., as described in more detail below). Multi-port graphics subsystem 627 may be configured to support different users on each port of multi-port graphics subsystem 627. For example, multi-port graphics subsystem 627 may be further configured to: support a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to multi-port graphics subsystem 627; support the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to multi-port graphics subsystem 627; and share graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to multi-port graphics subsystem 627.

[0178] In some embodiments of the device 620, for example, the collaboration engine 623 may further include a decoding sharer 628 (e.g., as described in more detail below). The decoding sharer 628 may be configured to: identify an overlap region of a shared scene between a first view region of a first user and a second view region of a second user; decode the overlap region; and share the decoded overlap region with both the first user and the second user. The decoding sharer 628 may also be configured to prioritize the decoding based on the overlap region.

[0179] The embodiments of each of the above processors 621, memory 622, collaboration engine 623, centralized sharer 624, depth sharer 625, shared preprocessor 626, multi-port graphics subsystem 627, decoding sharer 628, and other system components can be implemented in hardware, software, or any appropriate combination thereof. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technology such as ASIC, CMOS, or TTL technology, or any combination thereof. Alternatively or additionally, these components can be implemented in one or more modules as a set of logical instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components can be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0180] For example, device 620 may include similar components and / or features as system 100, further configured with a collaboration engine. For example, device 620 may additionally or alternatively include similar components and / or features as parallel processor 200, further configured with a collaboration engine as described herein. Device 620 may also be adapted to work with a stereo head mounted system, such as, for example, in combination with Figures 11 to 15 The system described.

[0181] Now turn to FIG. 6G to FIG. 6L , an embodiment of the method 630 of graphical collaboration may include: at box 631, identifying a shared graphical component between two or more users in an environment; and at box 632, sharing the shared graphical component with the two or more users in the environment.

[0182] In some embodiments, the method 630 may further include: at block 633, broadcasting the shared graphics component to all of the two or more users; and at block 634, individually allocating the individual graphics component to one of the two or more users. Some embodiments may also include: at block 635, splitting the workload of the shared graphics component based on a target virtual reality device.

[0183] In some embodiments, method 630 may further include: collecting depth information from a source independent of a first user of the two or more users at block 636; and sharing the depth information with the first user at block 637. The method may also include: collecting visibility information from the independent source outside the field of view of the first user at block 638; and sharing the visibility information with the first user at block 639.

[0184] In some embodiments, method 630 may further include: pre-calculating information related to the shared graphics component at block 640; and sharing the pre-calculated information with the two or more users at block 641. For example, at block 642, the pre-calculated information may include one or more of geometric information, primitive information, and physical information.

[0185] In some embodiments, method 630 may further include: supporting different users on each port of the multi-port graphics subsystem at block 643. For example, method 630 may include: supporting a left eye display and a right eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem at block 644; supporting the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem at block 645; and sharing graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem at block 646.

[0186] In some embodiments, method 630 may further include: identifying an overlap region of the shared scene between the first view region of the first user and the second view region of the second user at block 647; decoding the overlap region at block 648; and sharing the decoded overlap region with both the first user and the second user at block 649. At block 650, some embodiments may also include prioritizing the decoding based on the overlap region.

[0187] Embodiments of method 630 may be implemented in systems, devices, GPUs, parallel processing units (PPUs), or graphics processor pipeline devices such as those described herein. More specifically, the hardware implementation of method 630 may include configurable logic (such as, for example, PLA, FPGA, CPLD), or fixed-function logic hardware using circuit technology (such as, for example, ASIC, CMOS, or TTL technology), or any combination thereof. Alternatively or additionally, method 630 may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer-readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for performing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages. For example, method 630 may be implemented on a computer-readable medium as described below in conjunction with Examples 23 to 33.

[0188] For example, an embodiment or a portion of method 630 may be implemented using an application (e.g., through an API) or driver software. Other embodiments or portions of method 630 may be implemented using dedicated code (e.g., a shader) to be executed on a GPU. Other embodiments or portions of method 630 may be implemented using fixed-function logic or dedicated hardware (e.g., in a GPU).

[0189] Collaborative multi-user host / client example

[0190] The various embodiments of the multi-user collaborative VR system described herein can be implemented on various devices including server systems / host systems such as cloud services. Other host systems may include PCs, such as desktop computers, laptops, convertible computers, tablets, etc. In a VR scenario, the client system may include the user's HMD or other VR equipment for consuming content. In general, information from one source (e.g., a central source or other users) can be shared with users (e.g., to reduce the user's workload and / or enhance the user's experience). The user's system can therefore be configured to receive and use the shared information and / or merge the shared information with local and / or user-specific information.

[0191] Now turn to Figure 6M, an embodiment of the graphics device 670 may include: a processor 671; a memory 672, communicatively coupled to the processor 671; a collaboration engine 673, communicatively coupled to the processor 671 to receive the shared graphics component; and a synthesizer 674, communicatively coupled to the processor 671 to merge the shared graphics component with the separate graphics component. Some embodiments of the device 670 may further include a multi-port graphics subsystem 675 for supporting different users on each port.

[0192] Some embodiments of device 670 may further include: a wearable housing 676 to be worn by a user; and a display 677 communicatively coupled to processor 671, wherein display 677, processor 671, memory 672, cooperation interface 673, and synthesizer 674 may all be supported by wearable housing 676. For example, wearable housing 676 may be worn on a user's head, a user's neck, a user's shoulders, etc., wherein display 677 is positioned or positionable near the user's eyes.

[0193] In some embodiments, the collaboration interface 673 may be configured to broadcast information including shared graphics components. For example, the shared graphics components may include one or more of shared depth information, shared geometry information, and shared physical information. In some embodiments, the shared graphics components may include 360 ​​video content.

[0194] The embodiments of each of the processor 671, memory 672, collaboration interface 673, synthesizer 674, multi-port graphics subsystem 675, display 677, and other system components described above can be implemented in hardware, software, or any appropriate combination thereof. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technology such as ASIC, CMOS, or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0195] For example, device 670 may include similar components and / or features as system 100, further configured with a cooperative interface and synthesizer. For example, device 670 may additionally or alternatively include similar components and / or features as parallel processor 200, further configured with a cooperative interface and synthesizer as described herein. Device 670 may also be adapted to work with a stereo head mounted system, such as, for example, in combination with Figures 11 to 15 The system described.

[0196] Now turn to Figure 6N , the method 680 of graphics collaboration may include: at box 681, receiving a shared graphics component; and at box 682, merging the shared graphics component with the separate graphics component. The method 680 may further include: at box 683, providing a wearable housing to be worn by a user; and at box 684, using the wearable housing to support a display, a processor, a memory, a collaboration interface, and a synthesizer. For example, at box 685, the shared graphics component may include one or more of shared depth information, shared geometry information, and shared physical information, and / or at box 686, the shared graphics component may include 360 ​​video content. The method 680 may also include: at box 687, receiving broadcast information including the shared graphics component. Some embodiments may also include: at box 688, supporting different users on each port of the multi-port graphics subsystem.

[0197] Embodiments of method 680 may be implemented in systems, devices, GPUs, PPUs, or graphics processor pipeline devices such as those described herein. More specifically, the hardware implementation of method 680 may include configurable logic (such as, for example, PLA, FPGA, CPLD), or fixed-function logic hardware using circuit technology (such as, for example, ASIC, CMOS, or TTL technology), or any combination thereof. Alternatively or additionally, method 680 may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer-readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for performing the operations of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages. For example, method 680 may be implemented on a computer-readable medium as described below in conjunction with Examples 57 to 61.

[0198] For example, embodiments or portions of method 680 may be implemented using an application (e.g., via an API) or driver software. Other embodiments or portions of method 680 may be implemented using dedicated code (e.g., a shader) to be executed on a GPU. Other embodiments or portions of method 680 may be implemented using fixed-function logic or dedicated hardware (e.g., in a GPU).

[0199] Centralized Sharer Example

[0200] Now turn to Fig. 7A , the centralized sharing device 700 may include: a broadcaster 721 for broadcasting the shared graphics component to all two or more users; and a distributor 722, communicatively coupled to the broadcaster 721 so as to distribute the individual graphics component individually to one of the two or more users. Some embodiments of the device 700 may further include: a work splitter 723 for splitting the workload of the shared graphics component based on the target virtual reality device. Some embodiments of the device 700 may implement method 630 and / or method 680 (e.g., see Figure 6H and 6N ) part.

[0201] The embodiments of each of the above-mentioned broadcaster 721, distributor 722, work splitter 723 and other components of device 700 can be implemented in hardware, software or a combination thereof. For example, part or all of device 700 can be implemented as part of parallel processor 200, further configured with a broadcaster, distributor and / or work splitter as described herein. Device 700 can also be adapted to work with a stereo head-mounted system, such as, for example, in combination with Figures 11 to 15 The described system. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technologies such as ASIC, CMOS or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0202] Some embodiments may advantageously provide a centralized VR rendering framework that is broadcast among multiple users via wireless displays. For example, when multiple users interact in a shared VR environment, they can perform VR rendering on a central machine and broadcast the results to their wireless displays. The central machine can handle some common work and leave user-specific differences to each user's end unit to complete the final rendering.

[0203] For example, users on a theme park ride may view the same content for the most part, and this common work may be done at the centralized unit. In cases where users have different viewing angles, the centralized machine may handle any identified common work and leave some user-specific differences to each user's end unit to complete the final rendering. According to some embodiments, network bandwidth may be increased by using a common frequency for broadcasting information.

[0204] Some embodiments may provide a more efficient distribution model for the interaction between the graphics processor and one or more target HMDs. For example, instead of a point-to-point connection to each HMD, some embodiments may broadcast some elements to multiple users. Broadcasting shared content can save bandwidth compared to a point-to-point model. Even if each user has a different viewpoint, some useful information can still be shared. For example, some embodiments may use a centralized machine to broadcast shared information. Each user may also get a separate stream for their specific information / content. This information can be merged together locally for a complete, specific view for the user.

[0205] Some embodiments may identify common work versus user-specific work. For a common user experience (e.g., a theme park ride), there may be many common elements by design. Four users in a ride may see mostly the same scene from only slightly different angles, depending on their positions in the ride. The same content may be a shared component that may be broadcast to the users. Depending on the exact location of the user, this information may be interpolated and / or redirected to the user's viewpoint as needed. In some environments, the common work / shared components may be known in advance. The shared components may be rendered centrally, while the user-specific portions may be rendered locally. In some embodiments, specific work may also be rendered at a centralized location, but may be sent separately rather than broadcast. The user's device may be configured to merge the shared components and the user-specific portions.

[0206] In some embodiments, the shared information may be sent on a common link (e.g., the same frequency) for broadcast. Broadcasting may generally refer to sending the information only once and having all users receive the information. Identifying the shared components and sending the shared components once to all users may save bandwidth compared to sending the same or similar information multiple times to multiple users.

[0207] For the cycling example, users may see the background from slightly different angles. But for the purposes of increasing versatility and saving bandwidth, slight differences may be ignored. Some embodiments may render the background as a static image that does not tilt precisely with slight changes in viewpoint / orientation. A relatively static background can save a lot of bandwidth without causing a perceptible impact on the user experience. In some embodiments, the amount of change in viewpoint may be threshold-based. For example, if the viewpoint of the second user is within five degrees of the viewpoint of the first user, the same background may be provided. By design, some embodiments may not insist on ideal rendering of each user's viewpoint to save processing and / or network bandwidth. For example, for an augmented reality (AR) experience, AR objects may be rendered in the same orientation / position for more than one user even if the users' orientations / positions are not exactly the same.

[0208] For an installed AR / VR experience, multiple users may experience the experience on a regular basis. Although the experience changes from the perspective of a particular user as they experience the ride, there is another group of users that quickly enter the scene who will have a very similar experience as the previous user. Common information can be pre-rendered for individual positions and orientations. The user's HMD can then transmit their individual position and orientation information, and the centralized machine can transmit the appropriate scene information for this position and orientation.

[0209] For common components and specific components, some embodiments may be implemented in two stages. Some embodiments may render and / or broadcast common components together in the first stage and allocate specific components as needed in the second stage. Some embodiments may advantageously save bandwidth by broadcasting common components. A centralized shared processor (e.g., a GPU or an AR / VR processor) may identify common components of a scene and specific components of a scene, process common components when applicable, and broadcast the processed common components. The centralized shared processor may also allocate specific components. The user's AR / VR device (e.g., an HMD) may include a synthesizer for merging common components and specific components.

[0210] The centralized shared processor may process the shared components to varying degrees. In some cases, the centralized shared processor may render to the final display pixel. The common components may not be rendered to the final display pixel. The HMD may still perform some rendering or warping on the common components. For example, some common components may only correspond to common models and / or geometry. The centralized processor may defer some processing to the HMD, which may have better local information to complete the processing.

[0211] Some embodiments may include a work splitter for splitting common work based on the processing power of the HMD. For example, different HMDs may have different processing power and / or components to handle different graphics workloads. Simple HMDs may require a centralized shared processor to render to the final display pixels, while more complex HMDs may be able to handle more workloads. The centralized processor may be configured to identify the type of target HMD and adjust the workload accordingly.

[0212] Depth Sharer Example

[0213] Now turn to Fig. 8A , an embodiment of the depth sharing device 800 may include: a depth information collector 821 for collecting depth information from a source of a first user independent of two or more users; and a depth information sharer 822, communicatively coupled to the depth information collector 821 to share the depth information with the first user. Some embodiments of the device 800 may further include: a visibility information collector 823 for collecting visibility information from an independent source outside the field of view of the first user; and a visibility information sharer 824, communicatively coupled to the visibility information collector 823 to share the visibility information with the first user. Some embodiments of the device 800 may implement method 630 and / or method 680 (for example, see Fig.6I and 6N ) part.

[0214] The embodiments of each of the above-mentioned depth information collector 821, depth information sharer 822, visibility information collector 823, visibility information sharer 824, and other components of the device 800 can be implemented in hardware, software, or a combination thereof. For example, part or all of the device 800 can be implemented as part of the parallel processor 200, and further configured with the depth information collector, depth information sharer, visibility information collector, and / or visibility information sharer as described herein. The device 800 can also be adapted to work with a stereo head-mounted system, such as, for example, in combination with the following: Figures 11 to 15The described system. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technologies such as ASIC, CMOS or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0215] Now turn to Figure 8B , multiple users U 1 , U 2 , to U N You can operate AR / VR equipment (e.g., HMD 1 、HMD 2 , to HMD N )(e.g., where N>2). Multiple users may or may not be using the same application (e.g., playing the same game) and / or may or may not have the same AR / VR equipment. According to some embodiments, the AR / VR equipment may be configured to share information that may be useful to other users and / or receive shared information that may be useful to the AR / VR equipment.

[0216] Some embodiments may advantageously provide for distributed processing of depth camera data from multiple users. For example, if multiple AR users are in an environment, their AR devices may share depth camera information. Advantageously, each AR / VR system may not need to develop the entire scene separately. For example, if many users are using AR with depth cameras in a dense area (e.g., an urban environment), each AR device may transmit and receive (e.g., highly compressed) camera data to obtain higher accuracy and potentially lower processing power.

[0217] Some embodiments may improve the accuracy of positioning data. For example, a user's AR device may transmit depth information to a nearby neighboring AR device. Information communication may help with accuracy because nearby neighboring devices may have better depth readings of objects than the user's AR device. For example, a depth camera may have higher accuracy within a certain range. Some embodiments may advantageously use additional depth information from additional users to expand the range of the user's AR / VR system. Some embodiments may be able to provide less powerful cameras and / or turn off camera power based on the ability to share depth data (e.g., the lower the power, the lower the cost). Some embodiments may also save power by obtaining this information from other sources compared to developing information locally.

[0218] Other sources may also deliver depth information to the user's AR / VR device. Other sources may include, for example, static sources in the environment (e.g., fixed camera locations), autonomous sources in the environment (e.g., cameras on drones or autonomous vehicles), and / or sources outside the environment, such as cloud services. Some embodiments may utilize peer-to-peer sharing, centralized sharing, or both. For example, information about moving objects may be provided primarily from peer sources based on real-time perceived objects, while information about static objects may be provided from the cloud. Some embodiments may be configured to receive depth information from other sources (e.g., other users / cloud) and integrate the received depth information with local depth information.

[0219] For example, the depth information may be cluster-derived and stored in the cloud. The user's AR device may then download depth information (e.g., a 3D map) based on the user's position and orientation. The information may be provided with different degrees of resolution based on the available bandwidth and the user's AR device's ability to use the downloaded information. Cloud-based sharing of depth information may be useful for objects that may be relatively stable. For example, a user walking around an environment may generate depth information that may be uploaded to the cloud and saved. The uploaded depth information may be used to develop a 3D map for objects that are static in the environment. For example, some embodiments may use data analysis to determine static objects versus dynamic objects (e.g., after receiving the same data from 100 different users showing that the object has not changed, the object may be considered static). If a previously static object appears to have moved or is no longer confirmed to exist, the object may be removed from the cloud map.

[0220] In addition to or in lieu of enhanced distance / depth information, some embodiments may be able to provide information outside of the user's view to enhance the user's ability to see outside of their view or the view of their camera. For example, the user may be able to see occluding objects around corners or behind other objects, through walls, etc. If a person in front of the user blocks the user's view of a static object (e.g., a fire hydrant), the user may be alerted to the presence of the static object. The user may be able to see things behind people (e.g., they hide something from the user, but others see it or have seen it). For example, a police officer wearing AR glasses can see people hiding around corners or hidden weapons. Some embodiments may also provide a record of previous context in the scene (e.g., two minutes ago, there were five people in the alley).

[0221] Some embodiments may advantageously provide collaboration between multiple VR headsets. For example, multiple VR systems operating in an environment may share information. In a VR environment, it is likely that multiple users with VR headsets are looking at the same scene or geometry. For example, there may be multiple views of the same scene. Some embodiments may use collaboration / imaging between VR headsets to provide an enhanced user experience in situations where a user may be looking at something behind an opaque object or have different perspectives available to it.

[0222] Some embodiments may provide visibility behind physical objects. For example, in a gaming environment using VR cameras that share the same scene, the first user may be able to obtain the obstructed viewpoint from their perspective even if there is a physical object that obscures the viewpoint. Other users may provide view information behind the physical object to share with the first user. For example, other users may be looking at the area from different unobstructed angles. Other users may provide visibility information and this visibility information may be reflected into the HMD of the first user so that the first user can see things outside the physical object. The perspectives of other users may be extrapolated and redirected to the viewpoint of the first user. Some embodiments may include receiving information about the scene from one HMD, extrapolating the information to the orientation of other HMDs, and displaying redirection information on other HMDs.

[0223] Depending on available resources (e.g., storage devices, memory, and / or processing power), the area can be mapped based on the movement of individual users around the area so that even if no other user is currently looking at the area behind the object, the first user may be able to see what is behind the object (e.g., it may be a time-delayed view rather than a real-time view). Some embodiments may be useful for VR applications and / or AR applications. Some embodiments may be applicable to autonomous driving applications to expand the driver's view. For example, multiple vehicles can share information and provide the view to a driver who is overtaking a car, a side of a car, or behind a car. Dangers that may be outside the driver's current view can be provided to the driver. Danger images can be projected onto the windshield along with information about the distance to the hazard.

[0224] Shared Preprocessor Example

[0225] Now turn to Figure 8C , an embodiment of the shared preprocessor device 840 may include: a pre-calculator 841 for pre-calculating information related to the shared graphics component; and a pre-calculated information sharer 842 for sharing the pre-calculated information with two or more users. For example, the pre-calculated information may include one or more of geometric information, primitive information, and physical information. Some embodiments of the device 840 may implement the method 630 and / or the method 680 (e.g., see Figure 6J and 6N ) part.

[0226] The embodiments of each of the above-mentioned pre-calculation computer 841, pre-calculation information sharer 842, and other components of the device 840 can be implemented in hardware, software, or a combination thereof. For example, part or all of the device 840 can be implemented as part of the parallel processor 200, further configured with the pre-calculation computer and / or pre-calculation information sharer as described herein. The device 840 can also be adapted to work with a stereo head-mounted system, such as, for example, in combination with the following: Figures 11 to 15The described system. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technologies such as ASIC, CMOS or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0227] Now turn to Fig.8D , multiple users U 1 , U 2 , to U N You can operate AR / VR equipment (e.g., HMD 1 、HMD 2 , to HMD N )(e.g., where N>2). Multiple users may be using the same application and may or may not have the same AR / VR equipment. Advantageously, some embodiments may provide a decomposed shared simulation. In a multi-user environment, for example, several players may be experiencing a common AI or physics experience that may be pre-computed and distributed as part of a software development kit (SDK). In a multi-player game where multiple players are experiencing some of the same things, some embodiments may calculate some graphics information once and share the results among multiple players / HMDs or host devices (e.g., shared across multiple PCs, game consoles, etc.). Some embodiments may include a server for pre-computing common information (e.g., physics, AI, etc.) and then sharing the pre-computed information with multiple HMDs. For example, the pre-computed information may include object space information, geometry information, vertex information, texture information, shadow information, terrain information, and the like.

[0228] Multi-port Graphics Subsystem Example

[0229] Now turn to Fig.9A, an embodiment of the multi-port graphics subsystem 900 may include a first GPU 921 for a first display and a second GPU 922 for a second display. Some embodiments of the graphics subsystem 900 may have both the first GPU and the second GPU on the same substrate (e.g., die / SoC / package / printed circuit board), such as a discrete graphics card with multiple ports. Some embodiments of the graphics subsystem 900 may have the first GPU and the second GPU on different substrates, such as multiple discrete graphics cards and / or a combination of integrated graphics cards on a motherboard and discrete graphics cards, thereby supporting multiple ports between the various available GPUs.

[0230] According to some embodiments, the multi-port graphics subsystem 900 may be configured to support different users on each port of the multi-port graphics subsystem 900. For example, the multi-port graphics subsystem 900 may be configured to support a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem 900. The subsystem 900 may be further configured to: support the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem 900; and share graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem 900. Some embodiments of the subsystem 900 may implement method 630 and / or method 680 (e.g., see Figure 6K and 6N ) part.

[0231] The embodiments of each of the first GPU 921, the second GPU 922, and other components of the subsystem 900 described above may be implemented in hardware, software, or a combination thereof. For example, part or all of the subsystem 900 may be implemented as part of the parallel processor 200, further configured to support multiple users on multiple ports as described herein. The subsystem 900 may also be adapted to work with a stereo head-mounted system, such as in the following combination: Figures 11 to 15The described system. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technologies such as ASIC, CMOS or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0232] Now turn to Fig. 9B and Fig. 9C , the multi-port graphics subsystem 930 may include a first port 931 and a second port 932. When a first HMD 933 is attached to the graphics subsystem 930, the graphics subsystem 930 may support a left-eye display 934 and a right-eye display 935 of the first HMD 933. When both the first HMD 933 and the second HMD 936 are attached to the graphics subsystem 930, the graphics subsystem 930 may support an independent view on each of the first HMD 933 and the second HMD 936.

[0233] Advantageously, some embodiments may provide multi-user VR with two or more users. In some embodiments, instead of a left-eye display and a right-eye display, the graphics subsystem may support two users by reusing primitives, thereby supporting two HMDs. For example, in a dual graphics setup (e.g., a scalable link interface (SLI) or a discrete graphics card and an integrated graphics card), there may be enough bandwidth to render to two different HMDs. When there is only one HMD, the SLI / GPU is used to render the left view / right view. Some embodiments may advantageously share graphics components (e.g., geometry, primitives, content, textures, etc.) to render 3D content to two different HMDs with different content displayed in each HMD. Some embodiments may support a viewpoint with different "look" vectors, while some embodiments may support multiple independent viewpoints. Some embodiments may also support twitch, where one user can interact with VR using other users. For example, VR scenes may be broadcast or distributed for viewing by other users.

[0234] Some graphics cards may support multiple outputs, where a user may connect multiple HMDs to an output to get the same VR scene. Some embodiments may advantageously support different orientations of the connected HMDs through primitive sharing. For example, the system may render a 360-degree image, and each user may bring their own view into this 360-degree image. Some embodiments may make a determination about each user's position and field of view (e.g., what they are looking at), and identify information to share between users. In some embodiments, sharing may occur between an integrated GPU and a discrete GPU.

[0235] A user can plug multiple HMDs into the same GPU and use this GPU to render for both HMDs. Instead of having the graphics card support a left-eye display and a right-eye display, one graphics card can support two users. If two users are playing the same game (e.g., social VR or collaborative VR), the overlap between the users' scenes can be shared to efficiently utilize the GPU. For example, there may be one or more common geometries that do not need to be rendered repeatedly. These common geometries can be shared for each viewpoint, thereby reducing the workload on the GPU. When multiple GPUs are available (e.g., each user has his own GPU), splitting common geometries between multiple GPUs can reduce the workload of each GPU. Some embodiments can advantageously save power or increase available bandwidth for other GPU operations (e.g., increased detail for improving user experience).

[0236] For example, the first GPU can get lighting calculations, colors, levels, etc. for the first user's perspective. This information can be passed to the second GPU for use with the second user's different perspective. Some embodiments can save bandwidth on the second GPU by not having to retrieve this information from its own disk / memory. Some embodiments can use caches to share information on demand. Some embodiments can split the workload based on the processing power of the two GPUs. For example, the first GPU can get lighting calculations while the second GPU gets color information.

[0237] Some embodiments may have two graphics cards in one graphics subsystem to support one HMD, one for the left eye and one for the right eye. In some embodiments, this graphics subsystem may further support two HMDs. A user may connect one HMD to this one graphics card and another HMD to another graphics card. The graphics subsystem may support primitive sharing between the two graphics cards. Each card may render two eyes, but primitive sharing may still provide a good user experience while supporting two users instead of one.

[0238] Some embodiments may allow a group of users to play 360 videos from a cloud service (e.g., YOUTUBE or FACEBOOK) using multiple HMDs connected to different ports on the graphics card. For example, an integrated graphics system may include a VGA port and an HDMI port and / or a display port. These ports may be able to support multiple monitors simultaneously. Some embodiments may provide a driver to support multiple HMDs.

[0239] In some embodiments where the graphics card supports multiple outputs, each HMD may have its own viewport and viewing direction. In some applications, there may be one primary user who may be looking in one direction, while other viewers may be looking in a different direction. Some embodiments may be useful in some collaborative gaming where the viewer(s) may alert the primary user to activities occurring in the viewer(s)' field of view that the primary user may not be viewing.

[0240] Decode Sharer Example

[0241] Now turn to Fig. 10A , an embodiment of the decoding sharer 1000 may include: a region identifier 1021, for identifying an overlapping region of a shared scene between a first view region of a first user and a second view region of a second user; a decoder 1022, for decoding the overlapping region; and a region sharer 1023, for sharing the decoded overlapping region with both the first user and the second user. Some embodiments of the device 1000 may further include: a decoding priority sorter 1024, for prioritizing the decoding based on the overlapping region. Some embodiments of the device 1000 may implement method 630 and / or method 680 (for example, see Figure 6L and 6N ) part.

[0242] The above-mentioned embodiments of each of the zone identifier 1021, decoder 1022, zone sharer 1023, decoding priority sorter 1024, and other components of device 1000 can be implemented in hardware, software, or a combination thereof. For example, part or all of device 1000 can be implemented as part of parallel processor 200, further configured with the zone identifier, decoder 1022, zone sharer and / or decoding priority sorter as described herein. Device 1000 can also be adapted to work with a stereo head-mounted system, such as, for example, in combination with the following Figures 11 to 15The described system. For example, the hardware implementation may include configurable logic such as PLA, FPGA, CPLD, or fixed-function logic hardware using circuit technologies such as ASIC, CMOS or TTL technology, or any combination thereof. Alternatively or additionally, these components may be implemented in one or more modules as a set of logic instructions to be executed by a processor or computing device stored in a machine or computer readable storage medium such as RAM, ROM, PROM, firmware, flash memory, etc. For example, the computer program code for executing the operation of these components may be written in any combination of programming languages ​​applicable / suitable to one or more operating systems, including object-oriented programming languages ​​such as PYTHON, PERL, JAVA, SMALLTALK, C++, C#, and conventional procedural programming languages ​​such as "C" programming language or similar programming languages.

[0243] Now turn to Fig. 10B , the multi-port graphics subsystem 1030 may include a first port 1031, a second port 1032, a third port 1033, and a fourth port 1034. A first HMD 1035, a second HMD 1036, and a third HMD 1037 may all be attached to corresponding ports of the graphics subsystem 1030. The graphics subsystem 1030 may support independent views on each of the first HMD 1035, the second HMD 1036, and the third HMD 1037.

[0244] Now turn to FIG. 10C to FIG. 10D , the three HMDs may simultaneously view 360 frames 1040. For example, the first HMD 1035 may be positioned at a first viewpoint A, the second HMD 1036 may be positioned at a second viewpoint B, and the third HMD 1037 may be positioned at a third viewpoint C. The first viewpoint A and the second viewpoint B may include a first overlapping area 1041. The first viewpoint A and the third viewpoint C may include a second overlapping area 1042. The respective viewpoints and overlapping areas may change when the HMDs change positions.

[0245] Some embodiments may advantageously provide social 360 video rendering for multiple HMDs for VR applications. For example, some embodiments may perform multiple decodes for a GPU to support multiple users, where the hardware decode may render a portion of the field of view (FOV) of a 360 degree frame based on the orientation of each user. Multiple hardware decoding units may support multiple HMDs on a single stream (e.g., 360 video) for social VR. For example, some embodiments may support multiple viewports of 360 video and / or 360 twitch. Some embodiments may more efficiently implement 360 decoding of a single stream by sharing overlapping area decoding / encoding to avoid performing decoding / encoding multiple times on the same area and / or prioritizing decoding based on the amount of overlap.

[0246] Some systems may create a large rectangular frame for the 360 ​​video, encode the entire frame, and then provide this portion of the frame for display to the user based on the point the user is looking at. If a second user is watching the 360 ​​video, some systems may decode the second user's view based on where the second user is looking without reference to the first user, so that various regions may be decoded twice (e.g., or more times for more users with overlapping views). Some embodiments may advantageously identify overlapping regions of viewpoints for multiple users to avoid decoding the same region more than once.

[0247] Some embodiments may provide 360 ​​frames to a shared decoder. The shared decoder may take the position and orientation of the user as input. The first decoding of the first user may be stored in a first frame buffer (FB1). For the second user, the shared decoder may take into account the position and orientation of the second user in order to provide the second user with a second decoding stored in a second frame buffer (FB2). The shared decoder may determine the overlap between the two frame buffers to avoid repeated decoding. The shared decoder may prioritize decoding based on the presence of overlapping regions, and may reuse previously decoded portions of the frame. If multiple regions overlap, the shared decoder may process the overlapping regions first. If no one is viewing a particular region, the shared decoder may not decode the unviewed region at all.

[0248] In some embodiments, a host system (e.g., a PC, a server, etc.) may include a storage device for storing 360° videos. Multiple HMDs may be connected to the host system wired and / or wirelessly. For example, the host system may include a video card with multiple GPU slots. The host system may additionally or alternatively provide a gateway or router to support multiple HMDs. Multiple users of the HMD may each have their own view direction, and the host system may perform 360° decoding using shared and prioritized decoding for each user. In some embodiments, the video may be synchronized when provided to multiple users. For example, through cloud streaming, some embodiments may use multiple points to synchronize, so users may have a better shared experience.

[0249] Advantageously, some embodiments may not transmit the entire 360 ​​frame. Some embodiments may selectively decode based on what the user is viewing. If the HMD is connected via a cable, network bandwidth may not be as important, but some embodiments may still save processing bandwidth by selectively decoding and sharing the decoding of overlapping areas. For wireless HMDs, some embodiments may save network congestion and bandwidth by transmitting only a single decoded data.

[0250] Some embodiments may use multiple decoding blocks to decode a single 360 ​​frame. For example, a GPU may include an architecture with multiple decoding units configured to share overlapping decoding regions in the GPU. The position and orientation engine may merge the position and orientation information of all users to determine the overlap and provide the region to multiple decoding blocks. The GPU may take a 360 video, split it into multiple decodes, transcode, combine, and re-encode the information for each HMD.

[0251] Head-mounted display system overview

[0252] Fig.11 A head mounted display (HMD) system 1100 is shown to be worn by a user while experiencing an immersive environment, such as, for example, a virtual reality (VR) environment, an augmented reality (AR) environment, a multiplayer three-dimensional (3D) game, etc. In the example shown, one or more straps 1120 hold a frame 1102 of the HMD system 1100 in front of the user's eyes. Accordingly, a left eye display 1104 is positioned to be viewed by the user's left eye and a right eye display 1106 is positioned to be viewed by the user's right eye. In certain examples, such as, for example, a smartphone worn by a user, the left eye display 1104 and the right eye display 1106 may be optionally integrated into a single display. In the case of AR, the displays 1104, 1106 may be see-through displays that allow the user to view the physical environment while other rendered content (e.g., virtual characters, informational annotations, heads-up display / HUD) is presented above a live feed of the physical environment.

[0253] In one example, frame 1102 includes a left bottom looking camera 1108 to capture images from an area generally in front of the user and below the left eye (e.g., a left hand gesture). Additionally, a right bottom looking camera 1110 can capture images from an area generally in front of the user and below the right eye (e.g., a right hand gesture). The illustrated frame 1102 also includes a left front looking camera 1112 and a right front looking camera 1114 to capture images in front of the user's left and right eyes, respectively. Frame 1102 may also include a left side looking camera 1116 to capture images from an area to the left of the user and a right side looking camera 1118 to capture images from an area to the right of the user.

[0254] Images captured by cameras 1108, 1110, 1112, 1114, 1116, 1118, which may have overlapping fields of view, may be used to detect gestures made by the user and to analyze the external environment and / or reproduce the external environment on displays 1104, 1106. In one example, the detected gestures are used by a graphics processing architecture (e.g., internal and / or external) to render and / or control a virtual representation of the user in a 3D game. In fact, overlapping fields of view may enable the capture of gestures made by other individuals (e.g., in a multiplayer game), where the gestures of other individuals may also be used to render / control an immersive experience. Overlapping fields of view may also enable the HMD system 1100 to automatically detect obstructions or other impairments near the user. Such an approach is particularly advantageous in advanced driver assistance system (ADAS) applications.

[0255] In one example, a left bottom-looking camera 1108 and a right bottom-looking camera 1110 provided with overlapping fields of view provide a stereoscopic view with increased resolution. The increased resolution can in turn enable very similar user movements to be distinguished from each other (e.g., with sub-millimeter accuracy). The result can be an enhanced performance of the HMD system 1100 with respect to reliability. In fact, the solution shown is useful in a variety of applications, such as, for example, coloring information in an AR setting, exchanging virtual tools / devices between multiple users in a multi-user environment, rendering virtual items (e.g., weapons, swords, personnel), etc. The postures of other objects, limbs, and / or body parts can also be detected and used to render / control the virtual environment. For example, myelogram signals, electroencephalogram signals, eye tracking, breathing or panting, hand movements, etc. can be tracked in real time, whether from the wearer or from other individuals in a shared environment. Images captured by cameras 1108, 1110, 1112, 1114, 1116, 1118 can also be used as contextual input. For example, it may be determined that the user is indicating a specific word to be edited or a specific key to be pressed in a word processing application, a specific weapon to be deployed or a direction of travel in a game, and so on.

[0256] In addition, the images captured by the cameras 1108, 1110, 1112, 1114, 1116, 1118 can be used to implement shared communication or networked interaction in equipment operation, medical training and / or remote / teleoperation guidance applications. Task-specific gesture libraries or neural network machine learning can enable tool identification and feedback on tasks. For example, virtual tools converted into remote, real actions can be enabled. In another example, the HMD system 1100 converts the manipulation of a virtual drill in a virtual scene into remote operation of a drill on a robotic device deployed to search for collapsed buildings. Moreover, the HMD system 1100 can be programmable to the extent that it includes, for example, a protocol that enables a user to add a new gesture to a list of identifiable gestures associated with a user's action.

[0257] In addition, the various cameras in the HMD 1100 may be configurable to detect spectral frequencies outside of the visible wavelengths of the spectrum. The multispectral imaging capabilities of the input cameras allow for positional tracking of users and / or objects by eliminating non-essential image features (e.g., background noise). For example, in augmented reality (AR) applications such as surgery, instruments and equipment are tracked by their infrared reflectivity without the need for additional tracking aids. Moreover, the HMD 1100 may be employed in low-visibility situations, where "live feeds" from the various cameras may be enhanced or augmented by computer analysis and displayed to the user as visual or audio cues.

[0258] The HMD system 1100 may also forgo performing any type of data communication with a remote computing system or requiring a power cord (e.g., standalone operation mode). In this regard, the HMD system 1100 may be a "cordless" device having a power supply unit that enables the HMD system 1100 to operate independently of an external power system. Accordingly, a user may play a full-featured game without being tethered to another device (e.g., a game console) or a power supply. In a word processing example, the HMD system 1100 presents a virtual keyboard and / or a virtual mouse on displays 1104 and 1106 to provide a virtual desktop or word processing scene. Thus, the gesture identification data captured by one or more of the cameras represents a user typing activity on a virtual keyboard or a movement of a virtual mouse. Advantages include, but are not limited to, portability and privacy of a virtual desktop from nearby individuals. The underlying graphics processing architecture may support compression and / or decompression of video and audio signals. Moreover, providing separate images to the user's left and right eyes may assist in rendering, generation, and / or perception of 3D scenes. The relative positions of the left eye display 1104 and the right eye display 1106 may also be adjustable to match variations in interocular spacing between different users.

[0259] Fig.11 The number of cameras shown in FIG. 1 is only to facilitate discussion. In fact, depending on the environment, the HMD system 1100 may include less than six or more than six cameras.

[0260] Functional components of the HMD system

[0261] Fig.12The HMD system is shown in greater detail. In the example shown, the frame 1102 includes a power supply unit 1200 (e.g., battery power, adapter) that provides power to the HMD system. The shown frame 1102 also includes a motion tracking module 1220 (e.g., accelerometer, gyroscope), where the motion tracking module 1220 provides motion tracking data, orientation data, and / or position data to the processor system 1204. The processor system 1204 may include a network adapter 1224 coupled to the I / O bridge 1206. The I / O bridge 1206 can enable communication between the network adapter 1224 and various components such as, for example, the audio input module 1210, the audio output module 1208, the display device 1207, the input camera 1202, and the like.

[0262] In the example shown, the audio input module 1210 includes a right audio input 1218 and a left audio input 1216 that detect sounds that can be processed for the purpose of identifying voice commands of the user and nearby individuals. Voice commands identified in the captured audio signals can enhance gesture identification during modal switching and other applications. Moreover, the captured audio signals can provide 3D information for enhancing the immersive experience.

[0263] The audio output module 1208 may include a right audio output 1214 and a left audio output 1212. The audio output module 1208 may deliver sound to the ears of the user and / or other nearby individuals. The audio output module 1208 may be in the form of earplugs, on-ear speakers, cover-ear speakers, loudspeakers, etc. or any combination thereof, and the audio output module 1208 may deliver stereo and / or 3D audio content to the user (e.g., spatial positioning). The displayed frame 1102 also includes a wireless module 1222, which helps communication between the HMD system and various other systems (e.g., computers, wearable devices, game consoles). In one example, the wireless module 1222 communicates with the processor system 1204 via a network adapter 1224.

[0264] The display device 1207 shown includes a left eye display 1104 and a right eye display 1106, wherein virtual content presented on the displays 1104, 1106 may be obtained from the processor system 1204 via the I / O bridge 1206. The input cameras 1202 may include the left looking camera 1116, right looking camera 1118, lower left looking camera 1108, left front looking camera 1112, right front looking camera 1114, and lower right looking camera 1110 already discussed.

[0265] Now turn to Fig.13 , a general processing cluster (GPC) 1300 is shown. The GPC 1300 shown may be incorporated into a processor system 1204 ( Fig.12) in a processing system of a GPC 1300. GPC 1300 may include a pipeline manager 1302 that communicates with a scheduler. In one example, the pipeline manager 1302 receives tasks from the scheduler and distributes the tasks to one or more streaming multiprocessors (SMs) 1304. Each SM 1304 may be configured to process a thread group, where a thread group may be viewed as a plurality of related threads that perform the same or similar operations on different input data. Thus, each thread in a thread group may be assigned to a particular SM 1304. In another example, the number of threads may be greater than the number of execution units in SM 1304. In this regard, multiple threads in a thread group may operate in parallel. The pipeline manager 1302 may also specify the destination of processed data to a work distribution crossbar 1308, which communicates with a memory crossbar.

[0266] Thus, as each SM 1304 sends a processed task to the work distribution crossbar 1308, the processed task may be provided to another GPC 1300 for further processing. The output of the SM 1304 may also be sent to a pre-raster operation (preROP) unit 1314, which in turn directs the data to one or more raster operation units, or performs other operations (e.g., performing address translation, organizing picture color data, blending colors, etc.). The SM 1304 may include an internal first level (L1) cache (not shown) in which the SM 1304 may store data. The SM 1304 may also have access to a second level (L2) cache (not shown) and a first point five level (L1.5) cache 1306 via a memory management unit (MMU) 1310. The MMU 1310 may map virtual addresses to physical addresses. In this regard, the MMU 1310 may include page table entries (PTEs) used to map virtual addresses to physical addresses of tiles, memory pages, and / or cache line indexes. The GPU 1300 is shown to include a texture unit 1312 .

[0267] Graphics pipeline architecture

[0268] Now turn to Fig.14 , a graphics pipeline 1400 is shown. In the example shown, the world space pipeline 1420 includes a primitive distributor (PD) 1402. The PD 1402 may collect vertex data associated with high-order services, graphics primitives, triangles, etc., and send the vertex data to a vertex attribute fetch unit (VAF) 1404. The VAF 1404 may fetch vertex attributes associated with each incoming vertex from a shared memory and store the vertex data and the associated vertex attributes in the shared memory.

[0269] The illustrated world space pipeline 1420 also includes a vertex, tessellation, geometry processing unit (VTG) 1406. The VTG 1406 may include, for example, a vertex processing unit, a tessellation initialization processing unit, a task distributor, a task generation unit, a topology generation unit, a geometry processing unit, a tessellation processing unit, the like, or any combination thereof. In one example, the VTG 1406 is a programmable execution unit configured to execute geometry programs, tessellation programs, and vertex shader programs. The program executed by the VTG 1406 may process vertex data and vertex attributes received from the VAF 1404. Furthermore, the program executed by the VTG 1406 may generate graphics primitives, color values, surface normalization factors, and transparency values ​​at each vertex of the graphics primitives for further processing within the graphics processing pipeline 1400.

[0270] The vertex processing unit of VTG 1406 may be a programmable execution unit that executes a vertex shader program that specifies lighting and transforming vertex data. For example, the vertex processing unit may be programmed to transform vertex data from an object-based coordinate representation (e.g., object space) to an alternative object-based coordinate system such as world space or normalized device coordinate (NDC) space. In addition, the vertex processing unit may read vertex data and vertex attributes stored in a shared memory by VAF 1404 and process the vertex data and vertex attributes. In one example, the vertex processing unit stores the processed vertices in a shared memory.

[0271] The tessellation initialization processing unit (e.g., hull shader, tessellation control shader) may execute a tessellation initialization shader program. In one example, the tessellation initialization processing unit processes the vertices generated by the vertex processing unit and generates graphics primitives sometimes referred to as "patches". The tessellation initialization processing unit may also generate various patch attributes, wherein the patch data and patch attributes are stored in a shared memory. The task generation unit of the VTG 1406 may obtain data and attributes of vertices and patches from the shared memory. In one example, the task generation unit generates tasks for processing vertices and patches for processing by a later stage in the graphics processing pipeline 1400.

[0272] The tasks generated by the task generation unit may be redistributed by the task distributor of VTG 1406. For example, the tasks generated by various instances of the vertex shader program and the tessellation initialization program may differ significantly between one graphics processing pipeline 1400 and another. Accordingly, the task distributor may redistribute these tasks so that each graphics processing pipeline 1400 has approximately the same workload at later pipeline stages.

[0273] As already discussed, VTG 1406 may also include a topology generation unit. In one example, the topology generation unit obtains tasks distributed by the task distributor, indexes vertices including vertices associated with patches, and calculates tessellation vertices and coordinates (UVs) of indices that connect tessellation vertices to form graphics primitives. The indexed vertices may be stored in a shared memory by the topology generation unit. The tessellation processing unit of VTG 1406 may be configured to execute a tessellation shader program (e.g., a domain shader, a tessellation evaluation shader). The tessellation processing unit may read input data from the shared memory and write output data to the shared memory. The output data may be passed from the shared memory to a geometry processing unit (e.g., a next shader level) as input data.

[0274] The geometry processing unit of VTG 1406 may execute geometry shader programs to transform graphics primitives (e.g., triangles, line segments, points, etc.). In one example, vertices are grouped to construct graphics primitives, where the geometry processing unit subdivides the graphics primitives into one or more new graphics primitives. The geometry processing unit may also calculate parameters such as, for example, coefficients of plane equations that may be used to rasterize new graphics primitives.

[0275] The illustrated world space pipeline 1420 also includes a viewport scaling, picking, and clipping unit (VPC) 1408 that obtains parameters and vertices that specify new graphics primitives from the VTG 1406. In one example, the VPC 1408 performs clipping, flanging, perspective correction, and viewport transformation to identify graphics primitives that are potentially viewable in the final rendered image. The VPC 1408 may also identify graphics primitives that may not be viewable.

[0276] The graphics processing pipeline 1400 may also include a tiling unit 1410 coupled to the world space pipeline 1420. The tiling unit 1410 may be a graphics primitive sorting engine, wherein the graphics primitives are processed in the world space pipeline 1420 and then sent to the tiling unit 1410. In this regard, the graphics processing pipeline 1400 may also include a screen space pipeline 1422, wherein the screen space may be divided into cache tiles. Each cache tile may therefore be associated with a portion of the screen space. For each graphics primitive, the tiling unit 1410 may identify a set of cache tiles that intersect (e.g., tile) the graphics primitive. After tiling a number of graphics primitives, the tiling unit 1410 may process the graphics primitives cache tile by cache tile. In one example, the graphics primitives associated with a particular cache tile are sent to the setup unit 1412 in the screen space pipeline 1422 one tile at a time. A graphics primitive that intersects multiple cache tiles may be processed once in the world-space pipeline 1420 and sent to the screen-space pipeline 1422 multiple times.

[0277] In one example, the setup unit 1412 receives vertex data from the VPC 1408 via the blocking unit 1410 and calculates parameters associated with the graphics primitives. The parameters may include, for example, edge equations, partial plane equations, and depth plane equations. The screen space pipeline 1422 may also include a rasterizer 1414 coupled to the setup unit 1412. The rasterizer may scan-convert new graphics primitives and send fragments and coverage data to a pixel shading unit (PS) 1416. The rasterizer 1414 may also perform Z-picking and other Z-based optimizations.

[0278] The PS 1416, which can access the shared memory, can execute a fragment shader program that transforms the fragments received from the rasterizer 1414. More specifically, the fragment shader program can shade the fragments at a pixel level granularity (e.g., working as a pixel shader program). In another example, the fragment shader program shades the fragments at a sample level granularity, where each pixel includes multiple samples and each sample represents a portion of a pixel. Moreover, depending on the environment (e.g., the sampling rate), the fragment shader program can shade the fragments at any other granularity. The PS 1416 can perform color blending, shading, perspective correction, texture mapping, etc. to generate shaded fragments.

[0279] The illustrated screen space pipeline 1422 also includes a raster operations unit (ROP) 1418, which may perform operations such as, for example, stencil printing, Z testing, blending, etc. The ROP 1418 may then send the pixel data as processed graphics data to one or more rendered targets (e.g., graphics memory). The ROP 1418 may be configured to compress Z or color data written to memory and decompress Z or color data read from memory. The location of the ROP 1418 may vary depending on the environment.

[0280] Graphics processing pipeline 1400 may be implemented by one or more processing elements. For example, VTG 1406 and / or PS 1416 may be implemented in one or more SMs, and PD 1402, VAF 1408, blocking unit 1410, setup unit 1412, rasterizer 1414, and / or ROP 1418 may be implemented in a processing element of a specific GPC in conjunction with a corresponding partition unit. Graphics processing pipeline 1400 may also be implemented in fixed function hardware logic. In fact, graphics processing pipeline 1400 may be implemented in a PPU.

[0281] Thus, the illustrated world space pipeline 1420 processes graphics objects in 3D space, where the position of each graphics object relative to other graphics objects and relative to a 3D coordinate system is known. In contrast, the screen space pipeline 1422 can process graphics objects that have been projected from a 3D coordinate system onto a 2D planar surface representing the surface of a display device. In addition, the world space pipeline 1420 can be divided into an alpha stage pipeline and a beta stage pipeline, wherein the alpha stage pipeline includes pipeline stages from the PD 1402 to the task generation unit. The beta stage pipeline includes pipeline stages from the topology generation unit to the VPC 1408. In such a case, the graphics processing pipeline 1400 can perform a set of first operations (e.g., a single thread, a thread group, a plurality of thread groups acting in concert) in the alpha stage pipeline and perform a set of second operations (e.g., a single thread, a thread group, a plurality of thread groups acting in concert) in the beta stage pipeline.

[0282] If multiple graphics pipelines 1400 are in use, the vertex data and vertex attributes associated with a set of graphics objects may be partitioned so that each graphics processing pipeline 1400 has a similar workload throughout the alpha stage. Accordingly, the alpha stage processing may substantially expand the amount of vertex data and vertex attributes, so that the amount of vertex data and vertex attributes generated by the task generation unit is significantly greater than the amount of vertex data and vertex attributes processed by the PD 1402 and the VAF 1404. Furthermore, the task generation units associated with different graphics processing pipelines 1400 may generate vertex data and vertex attributes with different quality levels, even if the same number of attributes are used to start the alpha stage. In such a case, the task distributor may redistribute the attributes generated by the alpha stage pipeline, so that each graphics processing pipeline 1400 has approximately the same workload at the beginning of the beta stage pipeline.

[0283] Now turn to Fig.15, a streaming multiprocessor (SM) 1500 is shown. The SM 1500 shown includes K scheduler units 1504 coupled to an instruction cache 1502, wherein each scheduler unit 1504 receives a thread block array from a pipeline manager (not shown) and manages instruction scheduling for one or more thread blocks in each active thread block array. The scheduler unit 1504 can schedule threads for execution in parallel thread groups, wherein each group can be referred to as a "warp". Thus, each warp may include, for example, 64 threads. In addition, the scheduler unit 1504 can manage a plurality of different thread blocks, assigning thread blocks to warps for execution. The scheduler unit may then schedule instructions from the plurality of different warps on various functional units during each clock cycle. Each scheduler unit 1504 may include one or more instruction dispatch units 1522, wherein each dispatch unit 1522 sends instructions to one or more of the functional units. The number of dispatch units 1522 may vary depending on the environment. In the example shown, scheduler unit 1504 includes two dispatch units 1522 that cause two different instructions from the same warp to be dispatched during each clock cycle.

[0284] SM 1500 may also include a register file 1506. Register file 1506 includes a set of registers that are divided between functional units so that each functional unit is assigned a dedicated portion of register file 1506. Register file 1506 may also be divided between different thread warps being executed by SM 1500. In one example, register file 1506 provides temporary storage for operands of data paths connected to the functional units. The illustrated SM 1500 also includes L processing cores 1508, where L may be a relatively large number (e.g., 192). Each core 1508 may be a pipelined single-precision processing unit that includes a floating-point arithmetic logic unit (e.g., IEEE 754-2008) and an integer arithmetic logic unit.

[0285] The illustrated SM 1500 also includes M double precision units (DPUs) 1510, N special function units (SFUs) 1512, and P load / store units (LSUs) 1514. Each DPU 1510 can implement double precision floating point arithmetic and each SFU 1512 can perform special functions such as, for example, rectangular copy pixel blending. In addition, each LSU 1514 can implement load and store operations between shared memory 1518 and register file 1506. In one example, the load and store operations are implemented through J texture units / L1 caches 1520 and interconnect network 1516. In one example, the J texture units / L1 caches 1520 are also coupled to a crossbar switch (not shown). Therefore, the interconnect network 1516 can connect each of the functional units to the register file 1506 and the shared memory 1518. In one example, the interconnect network 1516 acts as a crossbar switch that connects any of the functional units to any register in the register file 1506.

[0286] SM 1500 may be implemented within a graphics processor (e.g., a graphics processing unit / GPU), where a texture unit / L1 cache 1520 may access a texture map from memory and sample the texture map to produce sampled texture values ​​for use in a shader program. Texture operations performed by the texture unit / L1 cache include, but are not limited to, mip map-based anti-aliasing.

[0287] Additional System Overview Examples

[0288] Fig.16 1 is a block diagram of a processing system 1600 according to an embodiment. In various embodiments, the system 1600 includes one or more processors 1602 and one or more graphics processors 1608, and may be a single-processor desktop computer system, a multi-processor workstation system, or a server system with a large number of processors 1602 or processor cores 1607. In one embodiment, the system 1600 is a processing platform included in a system-on-chip (SoC) for use in a mobile device, a handheld device, or an embedded device.

[0289] Embodiments of system 1600 may include or may be included in the following: a server-based game platform, a game console (including game and media consoles), a mobile game console, a handheld game console, or an online game console. In some embodiments, system 1600 is a mobile phone, a smart phone, a tablet computing device, or a mobile Internet device. Data processing system 1600 may also include, be coupled with, or be integrated in: a wearable device, such as a smart watch wearable device, a smart glasses device, an augmented reality device, or a virtual display device. In some embodiments, data processing system 1600 is a television or set-top box device having one or more processors 1602 and a graphics interface generated by one or more graphics processors 1608.

[0290] In some embodiments, one or more processors 1602 each include one or more processor cores 1607 for processing instructions, which when executed perform the operation of the system and user software. In some embodiments, each of the one or more processor cores 1607 is configured to process a specific instruction set 1609. In some embodiments, the instruction set 1609 can facilitate complex instruction set computing (CISC), reduced instruction set computing (RISC), or computing via very long instruction words (VLIW). Multiple processor cores 1607 can each process different instruction sets 1609, and the instruction set may include instructions for facilitating emulation of other instruction sets. The processor core 1607 may also include other processing devices, such as a digital signal processor (DSP).

[0291] In some embodiments, the processor 1602 includes a cache memory 1604. Depending on the architecture, the processor 1602 may have a single internal cache or multiple levels of internal cache. In some embodiments, the cache memory is shared among various components of the processor 1602. In some embodiments, the processor 1602 also uses an external cache (e.g., a level 3 (L3) cache or a last level cache (LLC) (not shown), which may be shared between the processor cores 1607 using known cache coherence techniques. A register file 1606 is additionally included in the processor 1602, which may include different types of registers (e.g., integer registers, floating point registers, status registers, and instruction pointer registers) for storing different types of data. Some registers may be general purpose registers, while other registers may be specific to the design of the processor 1602.

[0292] In some embodiments, the processor 1602 is coupled to a processor bus 1610 to transmit communication signals (e.g., address, data, or control signals) between the processor 1602 and other components in the system 1600. In one embodiment, the system 1600 uses an exemplary 'hub' system architecture, including a memory controller hub 1616 and an input-output (I / O) controller hub 1630. The memory controller hub 1616 facilitates communication between memory devices and other components of the system 1600, while the I / O controller hub (ICH) 1630 provides connections to the I / O devices via a local I / O bus. In one embodiment, the logic of the memory controller hub 1616 is integrated within the processor.

[0293] Memory device 1620 may be a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, a flash memory device, a phase change memory device, or some other memory device having suitable properties to act as process memory. In one embodiment, memory device 1620 may operate as system memory for system 1600 to store data 1622 and instructions 1621 for use when one or more processors 1602 execute applications or processes. Memory controller hub 1616 is also coupled to an optional external graphics processor 1612, which may be coupled to graphics processor 1608 in processor 1602 to perform graphics and media operations.

[0294] In some embodiments, the ICH 1630 enables peripheral devices to be connected to the memory device 1620 and the processor 1602 via a high-speed I / O bus. The I / O peripheral devices include, but are not limited to, an audio controller 1646, a firmware interface 1628, a wireless transceiver 1626 (e.g., Wi-Fi, Bluetooth), a data storage device 1624 (e.g., a hard drive, flash memory, etc.), and a traditional I / O controller 1640 for coupling traditional (e.g., Personal System 2 (PS / 2)) devices to the system. One or more Universal Serial Bus (USB) controllers 1642 connect input devices (e.g., a keyboard and mouse 1644 combination). A network controller 1634 may also be coupled to the ICH 1630. In some embodiments, a high-performance network controller (not shown) is coupled to the processor bus 1610. It will be appreciated that the system 1600 shown is exemplary and not limiting, as other types of data processing systems configured in different ways may also be used. For example, the I / O controller hub 1630 may be integrated within the one or more processors 1602 , or the memory controller hub 1616 and the I / O controller hub 1630 may be integrated within a discrete external graphics processor (such as the external graphics processor 1612 ).

[0295] Fig.17 is a block diagram of an embodiment of a processor 1700 having one or more processor cores 1702A- 1702N, an integrated memory controller 1714, and an integrated graphics processor 1708. Fig.17 Those elements having the same reference numbers (or names) as those of any other figure herein may operate or function in any manner similar to that described elsewhere herein, but are not limited thereto. Processor 1700 may include additional cores up to and including additional core 1702N represented by a dashed box. Each of processor cores 1702A to 1702N includes one or more internal cache units 1704A to 1704N. In some embodiments, each processor core is also capable of accessing one or more shared cache units 1706.

[0296] Internal cache units 1704A to 1704N and shared cache unit 1706 represent a cache memory hierarchy within processor 1700. The cache memory hierarchy may include at least one level of instruction and data cache within each processor core and one or more levels of shared intermediate level caches (e.g., level 2 (L2), level 3 (L3), level 4 (L4), or other levels of cache), where the highest level cache in front of external memory is classified as LLC. In some embodiments, cache coherence logic maintains coherence between the various cache units 1706 and 1704A to 1704N.

[0297] In some embodiments, the processor 1700 may further include a set of one or more bus controller units 1716 and a system agent core 1710. The one or more bus controller units 1716 manage a set of peripheral buses, such as one or more peripheral component interconnect buses (e.g., PCI, PCI Express buses). The system agent core 1710 provides management functions for various processor components. In some embodiments, the system agent core 1710 includes one or more integrated memory controllers 1714, which are used to manage access to various external memory devices (not shown).

[0298] In some embodiments, one or more of the processor cores 1702A to 1702N include support for simultaneous multithreaded processing. In such embodiments, the system agent core 1710 includes components for coordinating and operating the cores 1702A to 1702N during multithreaded processing. The system agent core 1710 may additionally include a power control unit (PCU) that includes logic and components for regulating the power state of the processor cores 1702A to 1702N and the graphics processor 1708.

[0299] In some embodiments, the processor 1700 further includes a graphics processor 1708 for performing graphics processing operations. In some embodiments, the graphics processor 1708 is coupled with a set of shared cache units 1706 and the system agent core 1710 including one or more integrated memory controllers 1714. In some embodiments, a display controller 1711 is coupled with the graphics processor 1708 to drive the graphics processor output to one or more coupled displays. In some embodiments, the display controller 1711 can be a separate module coupled to the graphics processor via at least one interconnect, or can be integrated within the graphics processor 1708 or the system agent core 1710.

[0300] In some embodiments, a ring-based interconnect unit 1712 is used to couple the internal components of the processor 1700. However, alternative interconnect units may be used, such as point-to-point interconnects, switched interconnects, or other technologies, including those well known in the art. In some embodiments, the graphics processor 1708 is coupled to the ring interconnect 1712 via an I / O link 1713.

[0301] Exemplary I / O links 1713 represent at least one of a variety of I / O interconnects, including an on-package I / O interconnect that facilitates communication between various processor components and high-performance embedded memory modules 1718, such as eDRAM modules. In some embodiments, each of processor cores 1702 to 1702N and graphics processor 1708 use embedded memory modules 1718 as a shared last-level cache.

[0302] In some embodiments, processor cores 1702A to 1702N are homogeneous cores that execute the same instruction set architecture. In another embodiment, processor cores 1702A to 1702N are heterogeneous in terms of instruction set architecture (ISA), wherein one or more of processor cores 1702A to 1702N execute a first instruction set, while at least one of the other cores executes a subset of the first instruction set or a different instruction value. In one embodiment, processor cores 1702A to 1702N are heterogeneous in terms of microarchitecture, wherein one or more cores with relatively higher power consumption are coupled with one or more power cores with lower power consumption. In addition, processor 1700 can be implemented on one or more chips or as a SoC integrated circuit having the components shown in addition to other components.

[0303] Fig.181 is a block diagram of a graphics processor 1800, which may be a discrete graphics processing unit, or may be a graphics processor integrated with multiple processing cores. In some embodiments, the graphics processor communicates with memory via a mapped I / O interface to registers on the graphics processor and using commands placed in processor memory. In some embodiments, the graphics processor 1800 includes a memory interface 1814 for accessing memory. The memory interface 1814 may be an interface to local memory, one or more internal caches, one or more shared external caches, and / or to system memory.

[0304] In some embodiments, the graphics processor 1800 also includes a display controller 1802 for driving display output data to a display device 1820. The display controller 1802 includes hardware for one or more overlapping planes of the display and a composition of multiple layers of video or user interface elements. In some embodiments, the graphics processor 1800 includes a video codec engine 1806 for encoding, decoding, or media transcoding to, from, or between one or more media encoding formats, including but not limited to: Moving Picture Experts Group (MPEG) formats (such as MPEG-2), Advanced Video Coding (AVC) formats (such as H.264 / MPEG-4 AVC), and Society of Motion Picture & Television Engineers (SMPTE) 421M / VC-1, and Joint Photographic Experts Group (JPEG) formats (such as JPEG, and Motion JPEG (MJPEG) formats).

[0305] In some embodiments, graphics processor 1800 includes a block image transfer (BLIT) engine 1804 for performing two-dimensional (2D) rasterizer operations, including, for example, bit boundary block transfers. However, in one embodiment, 2D graphics operations are performed using one or more components of a graphics processing engine (GPE) 1810. In some embodiments, graphics processing engine 1810 is a compute engine for performing graphics operations, including three-dimensional (3D) graphics operations and media operations.

[0306] In some embodiments, GPE 1810 includes a 3D pipeline 1812 for performing 3D operations, such as rendering three-dimensional images and scenes using processing functions that act on 3D primitive shapes (e.g., rectangles, triangles, etc.). 3D pipeline 1812 includes programmable and fixed function elements that perform various tasks within the elements and / or generated execution threads to 3D / media subsystem 1815. Although 3D pipeline 1812 can be used to perform media operations, embodiments of GPE 1810 also include a media pipeline 1816 that is specifically used to perform media operations, such as video post-processing and image enhancement.

[0307] In some embodiments, the media pipeline 1816 includes fixed-function or programmable logic units for performing one or more specialized media operations, such as video decoding acceleration, video deinterlacing, and video encoding acceleration, instead of or on behalf of the video codec engine 1806. In some embodiments, the media pipeline 1816 additionally includes a thread generation unit to generate threads for execution on the 3D / media subsystem 1815. The generated threads perform calculations for media operations on one or more graphics execution units included in the 3D / media subsystem 1815.

[0308] In some embodiments, the 3D / media subsystem 1815 includes logic for executing threads generated by the 3D pipeline 1812 and the media pipeline 1816. In one embodiment, the pipeline sends thread execution requests to the 3D / media subsystem 1815, which includes thread dispatch logic for arbitrating and dispatching each request to available thread execution resources. The execution resources include an array of graphics execution units for processing 3D and media threads. In some embodiments, the 3D / media subsystem 1815 includes one or more internal caches for thread instructions and data. In some embodiments, the subsystem also includes shared memory (including registers and addressable memory) to share data between threads and store output data.

[0309] 3D / Media Processing

[0310] Fig.19 is a block diagram of a graphics processing engine 1910 of a graphics processor according to some embodiments. In one embodiment, GPE 1910 is Fig.18 A version of the GPE 1810 shown in . Fig.19 Elements in FIG. 1 having the same reference number (or name) as elements of any other figure herein may operate or function in any manner similar to that described elsewhere herein, but are not limited thereto.

[0311] In some embodiments, the GPE 1910 is coupled to a command stream converter 1903, which provides a command stream to the 3D pipeline 1912 and the media pipeline 1916 of the GPE. In some embodiments, the command stream converter 1903 is coupled to a memory, which may be a system memory, or may be one or more of an internal cache memory and a shared cache memory. In some embodiments, the command stream converter 1903 receives commands from the memory and sends the commands to the 3D pipeline 1912 and / or the media pipeline 1916. The commands are instructions obtained from a ring buffer storing commands for the 3D pipeline 1912 and the media pipeline 1916. In one embodiment, the ring buffer may further include a batch command buffer storing multiple batches of multiple commands. The 3D pipeline 1912 and the media pipeline 1916 process the commands by performing operations via logic within the respective pipelines or by dispatching one or more execution threads to the execution unit array 1914. In some embodiments, execution unit array 1914 is scalable such that the array includes a variable number of execution units based on the target power and performance level of GPE 1910 .

[0312] In some embodiments, sampling engine 1930 is coupled to a memory (e.g., cache memory or system memory) and execution unit array 1914. In some embodiments, sampling engine 1930 provides a memory access mechanism for execution unit array 1914 that allows execution array 1914 to read graphics and media data from memory. In some embodiments, sampling engine 1930 includes logic for performing specialized image sampling operations for media.

[0313] In some embodiments, the specialized media sampling logic in the sampling engine 1930 includes a denoising / de-interlacing module 1932, a motion estimation module 1934, and an image scaling and filtering module 1936. In some embodiments, the denoising / de-interlacing module 1932 includes logic for performing one or more of a denoising or de-interlacing algorithm on the decoded video data. The de-interlacing logic combines the alternating lengths of the interlaced video content into a single frame of video. The denoising logic reduces or removes data noise from the video and image data. In some embodiments, the denoising and de-interlacing logic is motion adaptive and uses spatial or temporal filtering based on the amount of motion detected in the video data. In some embodiments, the denoising / de-interlacing module 1932 includes specialized motion detection logic (e.g., within the motion estimation engine 1934).

[0314] In some embodiments, the motion estimation engine 1934 provides hardware acceleration of video operations by performing video acceleration functions (such as motion vector estimation and prediction) on video data. The motion estimation engine determines motion vectors that describe image data transformations between consecutive video frames. In some embodiments, the graphics processor media codec uses the video motion estimation engine 1934 to perform operations on macroblock-level video that may otherwise be too computationally intensive to perform using a general-purpose processor. In some embodiments, the motion estimation engine 1934 may be generally available to the graphics processor component to assist in video decoding and processing functions that are sensitive or adaptive to the direction or magnitude of motion within the video data.

[0315] In some embodiments, the image scaling and filtering module 1936 performs image processing operations to improve the visual quality of the generated images and videos. In some embodiments, the scaling and filtering module 1936 processes the image and video data during a sampling operation before providing the data to the execution unit array 1914.

[0316] In some embodiments, GPE 1910 includes a data port 1944 that provides an additional mechanism for enabling the graphics subsystem to access memory. In some embodiments, data port 1944 facilitates memory access for operations including render target writes, constant buffer reads, temporary memory space reads / writes, and media surface accesses. In some embodiments, data port 1944 includes a cache memory space for caching accesses to memory. The cache memory can be a single data cache, or separated into multiple caches (e.g., render buffer caches, constant buffer caches, etc.) for multiple subsystems that access memory via data ports. In some embodiments, threads executing on execution units in execution unit array 1914 communicate with the data port by exchanging messages via a data distribution interconnect that couples each subsystem of GPE 1910.

[0317] Execution Unit

[0318] Fig. 20 is a block diagram of another embodiment of a graphics processor 2000 . Fig. 20 Elements in FIG. 1 having the same reference number (or name) as elements of any other figure herein may operate or function in any manner similar to that described elsewhere herein, but are not limited thereto.

[0319] In some embodiments, graphics processor 2000 includes ring interconnect 2002, pipeline front end 2004, media engine 2037, and graphics cores 2080A to 2080N. In some embodiments, ring interconnect 2002 couples the graphics processor to other processing units, including other graphics processors or one or more general-purpose processor cores. In some embodiments, the graphics processor is one of multiple processors integrated into a multi-core processing system.

[0320] In some embodiments, the graphics processor 2000 receives batches of commands via the ring interconnect 2002. The incoming commands are translated by the command stream converter 2003 in the pipeline front end 2004. In some embodiments, the graphics processor 2000 includes scalable execution logic for performing 3D geometry processing and media processing via the graphics cores 2080A to 2080N. For 3D geometry processing commands, the command stream converter 2003 supplies the commands to the geometry pipeline 2036. For at least some media processing commands, the command stream converter 2003 supplies the commands to the video front end 2034, which is coupled to the media engine 2037. In some embodiments, the media engine 2037 includes a video quality engine (VQE) 2030 for video and image post-processing and a multi-format encoding / decoding (MFX) 2033 engine for providing hardware accelerated media data encoding and decoding. In some embodiments, the geometry pipeline 2036 and the media engine 2037 each generate an execution thread, which is used for thread execution resources provided by at least one graphics core 2080A.

[0321] In some embodiments, the graphics processor 2000 includes scalable thread execution resources featuring modular cores 2080A to 2080N (sometimes referred to as core slices), each modular core having multiple sub-cores 2050A to 2050N, 2060A to 2060N (sometimes referred to as core sub-slices). In some embodiments, the graphics processor 2000 can have any number of graphics cores 2080A to 2080N. In some embodiments, the graphics processor 2000 includes a graphics core 2080A, which has at least a first sub-core 2050A and a second sub-core 2060A. In other embodiments, the graphics processor is a low-power processor with a single sub-core (e.g., 2050A). In some embodiments, the graphics processor 2000 includes multiple graphics cores 2080A to 2080N, each graphics core including a group of first sub-cores 2050A to 2050N and a group of second sub-cores 2060A to 2060N. Each of the group of first sub-cores 2050A to 2050N includes at least a first group of execution units 2052A to 2052N and a media / texture sampler 2054A to 2054N. Each of the group of second sub-cores 2060A to 2060N includes at least a second group of execution units 2062A to 2062N and a sampler 2064A to 2064N. In some embodiments, each sub-core 2050A to 2050N, 2060A-2060N shares a group of shared resources 2070A to 2070N. In some embodiments, these shared resources include shared cache memory and pixel operation logic. Other shared resources may also be included in various embodiments of the graphics processor.

[0322] Fig.21 Threadable execution logic 2100 is shown, including an array of processing elements employed in some embodiments of a GPE. Fig.21 Those elements in FIG. 1 having the same reference numbers (or names) as elements of any other figure herein may operate or function in any manner similar to that described elsewhere herein, but are not limited thereto.

[0323] In some embodiments, the thread execution logic 2100 includes a pixel shader 2102, a thread dispatcher 2104, an instruction cache 2106, a scalable execution unit array, including multiple execution units 2108A to 2108N, a sampler 2110, a data cache 2112, and a data port 2114. In one embodiment, these included components are interconnected via an interconnect structure that is linked to each of these components. In some embodiments, the thread execution logic 2100 includes one or more connections to a memory (e.g., a system memory or a cache memory) through the instruction cache 2106, the data port 2114, the sampler 2110, and one of the execution unit arrays 2108A to 2108N. In some embodiments, each execution unit (e.g., 2108A) is an individual vector processor capable of executing multiple simultaneous threads and processing multiple data elements in parallel for each thread. In some embodiments, the execution unit arrays 2108A to 2108N include any number of individual execution units.

[0324] In some embodiments, execution unit arrays 2108A to 2108N are primarily used to execute "shader" programs. In some embodiments, the execution units in arrays 2108A to 2108N execute an instruction set that includes native support for many standard 3D graphics shader instructions, so that shader programs from graphics libraries (e.g., Direct 3D and OpenGL) are executed with minimal conversion. The execution units support vertex and geometry processing (e.g., vertex programs, geometry programs, vertex shaders), pixel processing (e.g., pixel shaders, fragment shaders), and general processing (e.g., compute and media shaders).

[0325] Each execution unit in the execution unit array 2108A to 2108N operates on an array of data elements. The number of data elements is the "execution size" or number of lanes for the instruction. An execution lane is a logical execution unit used for data element access, masking, and flow control within an instruction. The number of lanes may be independent of the number of physical arithmetic logic units (ALUs) or floating point units (FPUs) for a particular graphics processor. In some embodiments, execution units 2108A to 2108N support integer and floating point data types.

[0326] The execution unit instruction set includes single instruction multiple data (SIMD). Various data elements can be stored in registers as compressed data types, and the execution unit will process these elements based on the data size of various elements. For example, when operating on a 256-bit wide vector, the 256-bit vector is stored in a register, and the execution unit operates on the vector as four independent 64-bit compressed data elements (data elements of quadruple word length (QW) size), eight independent 32-bit compressed data elements (data elements of double word length (DW) size), sixteen independent 16-bit compressed data elements (data elements of word length (W) size), or thirty-two independent 8-bit data elements (data elements of byte (B) size). However, different vector widths and register sizes are possible.

[0327] One or more internal instruction caches (e.g., 2106) are included in the thread execution logic 2100 to cache thread instructions for the execution unit. In some embodiments, one or more data caches (e.g., 2112) are included to cache thread data during thread execution. In some embodiments, a sampler 2110 is included to provide texture sampling for 3D operations and media sampling for media operations. In some embodiments, the sampler 2110 includes a specialized texture or media sampling function to process texture or media data during the sampling process before providing the sampled data to the execution unit.

[0328] During execution, the graphics pipeline and the media pipeline send thread initiation requests to the thread execution logic 2100 via the thread generation and dispatch logic. In some embodiments, the thread execution logic 2100 includes a local thread dispatcher 2104 that arbitrates thread initiation requests from the graphics pipeline and the media pipeline and instantiates the requested threads on one or more execution units 2108A to 2108N. For example, the geometry pipeline (e.g., Fig. 20 2036) dispatches vertex processing, tessellation or geometry processing threads to thread execution logic 2100 ( Fig.21 ). In some embodiments, thread dispatcher 2104 may also process runtime thread generation requests from executing shader programs.

[0329] Once a set of geometric objects has been processed and rasterized into pixel data, the pixel shader 2102 is called to further calculate output information and cause the results to be written to the output surface (e.g., color buffer, depth buffer, stencil buffer, etc.). In some embodiments, the pixel shader 2102 calculates the value of each vertex attribute, which is interpolated across the rasterized object. In some embodiments, the pixel shader 2102 then executes a pixel shader program supplied by an application programming interface (API). In order to execute the pixel shader program, the pixel shader 2102 dispatches threads to execution units (e.g., 2108A) via a thread dispatcher 2104. In some embodiments, the pixel shader 2102 uses texture sampling logic in a sampler 2110 to access texture data in a texture map stored in a memory. Arithmetic operations performed on the texture data and the input geometry calculate pixel color data for each geometric fragment, or discard one or more pixels for further processing.

[0330] In some embodiments, data port 2114 provides a memory access mechanism for thread execution logic 2100 to output processed data to memory for processing on the graphics processor output pipeline. In some embodiments, data port 2114 includes or is coupled to one or more cache memories (e.g., data cache 2112) to cache data via the data port for memory access.

[0331] Fig. 22 is a block diagram of a schematic graphics processor instruction format 2200 according to some embodiments. In one or more embodiments, the graphics processor execution unit supports an instruction set having instructions in multiple formats. Solid line boxes show components that are typically included in execution unit instructions, while dashed lines include components that are optional or included only in a subset of instructions. In some embodiments, the instruction format 2200 described and illustrated are macroinstructions because they are instructions supplied to the execution unit, as opposed to micro-operations generated from instruction decoding (once the instruction is processed).

[0332] In some embodiments, the graphics processor execution unit natively supports instructions in 128-bit format 2210. 64-bit compact instruction format 2230 can be used for some instructions based on the selected instruction, instruction options and the number of operands. Native 128-bit format 2210 provides access to all instruction options, while some options and operations are restricted in 64-bit format 2230. The native instructions available in 64-bit format 2230 vary according to the embodiment. In some embodiments, instructions are partially compacted using a set of index values ​​in index field 2213. The execution unit hardware references a set of compression tables based on these index values, and uses the compression table output to reconstruct the native instructions in 128-bit format 2210.

[0333] For each format, the instruction opcode 2212 defines the operation to be performed by the execution unit. The execution unit executes each instruction in parallel across multiple data elements of each operand. For example, in response to an addition instruction, the execution unit executes simultaneous addition operations across each color channel representing a texture element or a picture element. By default, the execution unit executes each instruction across all data channels of the operand. In some embodiments, the instruction control field 2214 enables control of certain execution options, such as channel selection (e.g., prediction) and data channel sorting (e.g., mixing). For 128-bit instructions 2210, the execution size field 2216 limits the number of data channels that will be executed in parallel. In some embodiments, the execution size field 2216 is not available for 64-bit compact instruction format 2230.

[0334] Some execution unit instructions have up to three operands, including two source operands src0 2220, src1 2222, and one destination 2218. In some embodiments, the execution unit supports dual destination instructions, where one of the destinations is implicit. Data manipulation instructions may have a third source operand (e.g., SRC2 2224), where the instruction opcode 2212 determines the number of source operands. The last source operand of an instruction may be an immediate (e.g., hard-coded) value passed by the instruction.

[0335] In some embodiments, the 128-bit instruction format 2210 includes access / address mode information 2226, which specifies, for example, whether direct register addressing mode or indirect register addressing mode is used. When direct register addressing mode is used, the register address of one or more operands is provided directly by bits in the instruction 2210.

[0336] In some embodiments, the 128-bit instruction format 2210 includes an access / address mode field 2226 that specifies the address mode and / or access mode of the instruction. In one embodiment, the access mode defines the data access alignment of the instruction. Some embodiments support access modes including a 16-byte aligned access mode and a 1-byte aligned access mode, wherein the byte alignment of the access mode determines the access alignment of the instruction operand. For example, when in a first mode, the instruction 2210 may use byte-aligned addressing for source operands and destination operands, and when in a second mode, the instruction 2210 may use 16-byte aligned addressing for all source operands and destination operands.

[0337] In one embodiment, the address mode portion of the access / address mode field 2226 determines whether the instruction will use direct addressing or indirect addressing. When direct register addressing mode is used, the bits in the instruction 2210 directly provide the register address of one or more operands. When indirect register addressing mode is used, the register address of one or more operands can be calculated based on the address register value and the address immediate field in the instruction.

[0338] In some embodiments, instructions are grouped based on the opcode 2212 bit field to simplify opcode decoding 2240. For 8-bit opcodes, bits 4, 5, and 6 allow the execution unit to determine the type of opcode. The precise opcode grouping shown is exemplary only. In some embodiments, the move and logic opcode group 2242 includes data movement and logic instructions (e.g., move (mov), compare (cmp)). In some embodiments, the move and logic group 2242 shares five most significant bits (MSBs), wherein the move (mov) instruction adopts the form of 0000xxxxb, and the logic instruction adopts the form of 0001xxxxb. The flow control instruction group 2244 (e.g., call (call), jump (jmp)) includes instructions in the form of 0010xxxxb (e.g., 0x20). The miscellaneous instruction group 2246 includes a mixture of instructions, which include synchronization instructions (e.g., wait, send) in the form of 0011xxxxb (e.g., 0x30). The parallel math instruction group 2248 includes component-wise arithmetic instructions (e.g., add, mul) in the form of 0100xxxxb (e.g., 0x40). The parallel math group 2248 performs arithmetic operations in parallel across data lanes. The vector math group 2250 includes arithmetic instructions (e.g., dp4) in the form of 0101xxxxb (e.g., 0x50). The vector math group performs arithmetic such as dot product calculations on vector operands.

[0339] Graphics Pipeline

[0340] Fig.23 is a block diagram of another embodiment of a graphics processor 2300 . Fig.23 Elements in FIG. 1 having the same reference number (or name) as elements of any other figure herein may operate or function in any manner similar to that described elsewhere herein, but are not limited thereto.

[0341] In some embodiments, the graphics processor 2300 includes a graphics pipeline 2320, a media pipeline 2330, a display engine 2340, a thread execution logic 2350, and a rendering output pipeline 2370. In some embodiments, the graphics processor 2300 is a graphics processor within a multi-core processing system that includes one or more general-purpose processing cores. The graphics processor is controlled by register writes to one or more control registers (not shown) or by commands issued to the graphics processor 2300 via the ring interconnect 2302. In some embodiments, the ring interconnect 2302 couples the graphics processor 2300 to other processing components, such as other graphics processors or general-purpose processors. Commands from the ring interconnect 2302 are translated by a command stream converter 2303, which supplies instructions to individual components of the graphics pipeline 2320 or the media pipeline 2330.

[0342] In some embodiments, the command stream converter 2303 directs the operation of the vertex fetcher 2305, which reads vertex data from memory and executes vertex processing commands provided by the command stream converter 2303. In some embodiments, the vertex fetcher 2305 provides the vertex data to the vertex shader 2307, which performs coordinate space transformation and lighting operations on each vertex. In some embodiments, the vertex fetcher 2305 and the vertex shader 2307 execute the vertex processing instructions by dispatching execution threads to the execution units 2352A, 2352B via the thread dispatcher 2331.

[0343] In some embodiments, execution units 2352A, 2352B are arrays of vector processors with instruction sets for performing graphics and media operations. In some embodiments, execution units 2352A, 2352B have an additional L1 cache 2351 specific for each array or shared between arrays. The cache can be configured as a data cache, an instruction cache, or a single cache that is partitioned to contain data and instructions in different partitions.

[0344] In some embodiments, the graphics pipeline 2320 includes a tessellation component for performing hardware accelerated tessellation of 3D objects. In some embodiments, a programmable hull shader 2311 configures the tessellation operation. A programmable domain shader 2317 provides back-end evaluation of the tessellation output. The tessellation 2313 operates at the direction of the hull shader 2311 and contains dedicated logic for generating a detailed set of geometric objects based on a coarse geometric model that is provided as input to the graphics pipeline 2320. In some embodiments, if tessellation is not used, the tessellation components 2311, 2313, 2317 can be bypassed.

[0345] In some embodiments, the complete geometric object may be processed by the geometry shader 2319 via one or more threads dispatched to the execution units 2352A, 2352B, or may proceed directly to the clipper 2329. In some embodiments, the geometry shader operates on entire geometric objects (rather than vertices or vertex patches as in previous stages of the graphics pipeline). If tessellation is disabled, the geometry shader 2319 receives input from the vertex shader 2307. In some embodiments, the geometry shader 2319 may be programmed by a geometry shader program to perform geometry tessellation when the tessellation unit is disabled.

[0346] Prior to rasterization, the clipper 2329 processes the vertex data. The clipper 2329 can be a fixed function clipper or a programmable clipper with clipping and geometry shader functions. In some embodiments, a rasterizer 2373 (e.g., a depth test component) in the render output pipeline 2370 dispatches a pixel shader to convert geometric objects into their pixel-by-pixel representations. In some embodiments, the pixel shader logic is included in the thread execution logic 2350. In some embodiments, the application can bypass the rasterizer 2373 and access the unrasterized vertex data via the outflow unit 2323.

[0347] The graphics processor 2300 has an interconnect bus, interconnect structure, or some other interconnect mechanism that allows data and messages to be passed among the main components of the processor. In some embodiments, the execution units 2352A, 2352B and associated cache(s) 2351, texture and media samplers 2354, and texture / sampler cache 2358 are interconnected via data ports 2356 to perform memory accesses and communicate with the rendering output pipeline components of the processor. In some embodiments, the samplers 2354, caches 2351, 2358, and execution units 2352A, 2352B each have separate memory access paths.

[0348] In some embodiments, the rendering output pipeline 2370 includes a rasterizer 2373 that converts vertex-based objects into associated pixel-based representations. In some embodiments, the rasterizer logic includes a windower / masker unit for performing fixed-function triangle and line rasterization. An associated rendering cache 2378 and depth cache 2379 are also available in some embodiments. The pixel operation component 2377 performs pixel-based operations on data, although in some examples, pixel operations associated with 2D operations (e.g., bit block image transfers and blending) are performed by the 2D engine 2341, or replaced by a display controller 2343 using overlapping display planes at display time. In some embodiments, a shared L3 cache 2375 can be used for all graphics components, allowing data to be shared without using main system memory.

[0349] In some embodiments, the graphics processor media pipeline 2330 includes a media engine 2337 and a video front end 2334. In some embodiments, the video front end 2334 receives pipeline commands from the command stream converter 2303. In some embodiments, the media pipeline 2330 includes a separate command stream converter. In some embodiments, the video front end 2334 processes the media commands before sending the commands to the media engine 2337. In some embodiments, the media engine 2337 includes a thread generation function for generating threads for dispatching to the thread execution logic 2350 via the thread dispatcher 2331.

[0350] In some embodiments, the graphics processor 2300 includes a display engine 2340. In some embodiments, the display engine 2340 is external to the processor 2300 and is coupled to the graphics processor via the ring interconnect 2302, or some other interconnect bus or structure. In some embodiments, the display engine 2340 includes a 2D engine 2341 and a display controller 2343. In some embodiments, the display engine 2340 includes dedicated logic that can operate independently of the 3D pipeline. In some embodiments, the display controller 2343 is coupled to a display device (not shown), which can be a system-integrated display device (such as in a laptop computer), or can be an external display device attached via a display device connector.

[0351] In some embodiments, graphics pipeline 2320 and media pipeline 2330 can be configured to perform operations based on multiple graphics and media programming interfaces, and are not specific to any one application programming interface (API). In some embodiments, the driver software of the graphics processor converts the API dispatch specific to a specific graphics or media library into a command that can be processed by the graphics processor. In some embodiments, the open graphics library (OpenGL) and open computing language (OpenCL) from Khronos Group, the Direct 3D library from Microsoft Corporation provide support, or both OpenGL and D3D can be provided. It is also possible to provide support for the open source computer vision library (OpenCV). If it is possible to map the pipeline called from the future API to the pipeline of the graphics processor, then the future API with a compatible 3D pipeline will also be supported.

[0352] Graphics Pipeline Programming

[0353] Fig.24A is a block diagram of a schematic diagram of a processor command format 2400 according to some embodiments. Fig. 24B is a block diagram illustrating a schematic diagram of a processor command sequence 2410 according to an embodiment. Fig.24A The solid-line boxes in show components that are typically included in a graphics command, while the dashed lines include components that are optional or included only in a subset of graphics commands. Fig.24A The exemplary graphics processor command format 2400 includes data fields for identifying the target client 2402 of the command, a command operation code (opcode) 2404, and command related data 2406. In some commands, a sub-opcode 2405 and a command size 2408 are also included.

[0354] In some embodiments, client 2402 specifies the client unit of the graphics device that processes the command data. In some embodiments, the graphics processor command parser checks the client field of each command to adjust the further processing of the command and routes the command data to the appropriate client unit. In some embodiments, the graphics processor client unit includes a memory interface unit, a rendering unit, a 2D unit, a 3D unit, and a media unit. Each client unit has a corresponding processing pipeline for processing commands. Once the command is received by the client unit, the client unit reads the opcode 2404 and (if present) the sub-opcode 2405 to determine the operation to be performed. The client unit uses the information in the data field 2406 to execute the command. For some commands, an explicit command size 2408 is expected to specify the size of the command. In some embodiments, the command parser automatically determines the size of at least some of the commands in the command based on the command opcode. In some embodiments, the commands are aligned via multiples of the double word length.

[0355] Fig. 24B An exemplary graphics processor command sequence 2410 is shown in the flowchart of FIG. In some embodiments, software or firmware of a data processing system featuring an embodiment of a graphics processor uses a version of the command sequence shown to initiate, execute, and terminate a set of graphics operations. The sample command sequence is shown and described for exemplary purposes only, as embodiments are not limited to these particular commands or this command sequence. In addition, the commands may be issued as a batch of commands in a command sequence so that the graphics processor will process the command sequence in an at least partially simultaneous manner.

[0356] In some embodiments, the graphics processor command sequence 2410 may begin with a pipeline dump clear command 2412 to cause any active graphics pipeline to complete the currently pending commands of the pipeline. In some embodiments, the 3D pipeline 2422 and the media pipeline 2424 are not operating at the same time. The pipeline dump clear is performed to cause the active graphics pipeline to complete any pending commands. In response to the pipeline dump clear, the command parser of the graphics processor will suspend command processing until the active drawing engine completes the pending operation and the associated read cache is invalidated. Optionally, any data marked as 'dirty' in the rendering cache can be dumped to memory. In some embodiments, the pipeline dump clear command 2412 can be used for pipeline synchronization or before placing the graphics processor in a low power state.

[0357] In some embodiments, when a command sequence requires the graphics processor to explicitly switch between pipelines, a pipeline select command 2413 is used. In some embodiments, a pipeline select command 2413 is only required once in an execution context before issuing pipeline commands, unless the context is to issue commands for both pipelines. In some embodiments, a pipeline flush command is 2412 is required immediately before a pipeline switch is made via a pipeline select command 2413.

[0358] In some embodiments, pipeline control commands 2414 configure the graphics pipeline for operation and are used to program 3D pipeline 2422 and media pipeline 2424. In some embodiments, pipeline control commands 2414 configure the pipeline state of the active pipeline. In one embodiment, pipeline control commands 2414 are used for pipeline synchronization and for clearing data from one or more cache memories within the active pipeline before processing a batch of commands.

[0359] In some embodiments, a set of return buffers for the corresponding pipeline to write data is configured using return buffer state commands 2416. Some pipeline operations require the allocation, selection, or configuration of one or more return buffers into which these operations write intermediate data during processing. In some embodiments, the graphics processor also uses one or more return buffers to store output data and perform cross-thread communication. In some embodiments, return buffer state 2416 includes selecting the size and number of return buffers to use for a set of pipeline operations.

[0360] The remaining commands in the command sequence differ based on the active pipeline for operation. Based on pipeline determination 2420 , the command sequence is customized according to a 3D pipeline 2422 , which starts at 3D pipeline state 2430 , and a media pipeline 2424 , which starts at media pipeline state 2440 .

[0361] The commands for 3D pipeline state 2430 include 3D state setting commands for vertex buffer state, vertex element state, constant color state, depth buffer state, and other state variables that will be configured before processing 3D primitive commands. The values ​​of these commands are determined based at least in part on the specific 3D API in use. In some embodiments, the 3D pipeline state 2430 commands can also selectively disable or bypass specific pipeline elements if those elements will not be used.

[0362] In some embodiments, 3D primitive 2432 commands are used to submit 3D primitives to be processed by 3D pipeline. The commands and associated parameters passed to the graphics processor via 3D primitive 2432 are forwarded to the vertex acquisition function in the graphics pipeline. The vertex acquisition function uses 3D primitive 2432 command data to generate vertex data structure. The vertex data structure is stored in one or more return buffers. In some embodiments, 3D primitive 2432 commands are used to perform vertex operations on 3D primitives via vertex shaders. In order to process vertex shaders, 3D pipeline 2422 dispatches shader execution threads to the graphics processor execution unit.

[0363] In some embodiments, the 3D pipeline 2422 is triggered via an execution 2434 command or event. In some embodiments, a register write triggers the command execution. In some embodiments, the execution is triggered via a 'go' or 'kick' command in a command sequence. In one embodiment, the command execution is triggered using a pipeline synchronization command to dump and clear the command sequence through the graphics pipeline. The 3D pipeline will perform geometry processing for 3D primitives. Once the operation is completed, the resulting geometric object is rasterized, and the pixel engine colors the resulting pixels. Additional commands for controlling pixel shading and pixel backend operations may also be included for those operations.

[0364] In some embodiments, when performing media operations, the graphics processor command sequence 2410 follows the media pipeline 2424 path. Generally, the specific purpose and programming of the media pipeline 2424 depends on the media or computing operation to be performed. During media decoding, specific media decoding operations can be offloaded to the media pipeline. In some embodiments, the media pipeline can also be bypassed, and the media decoding can be performed in whole or in part using resources provided by one or more general processing cores. In one embodiment, the media pipeline also includes elements for general purpose graphics processor unit (GPGPU) operations, wherein the graphics processor is used to perform SIMD vector operations using compute shader programs, and the compute shader programs are not explicitly related to the rendering of graphics primitives.

[0365] In some embodiments, the media pipeline 2424 is configured in a similar manner to the 3D pipeline 2422. A set of media pipeline state commands 2440 are dispatched or placed into a command queue prior to the media object commands 2442. In some embodiments, the media pipeline state commands 2440 include data for configuring the media pipeline elements that will be used to process the media objects. This includes data for configuring the video decoding and video encoding logic within the media pipeline (such as encoding or decoding modes). In some embodiments, the media pipeline state commands 2440 also support the use of one or more pointers to an "indirect" state element that contains a batch of state settings.

[0366] In some embodiments, media object commands 2442 supply pointers to media objects for processing by the media pipeline. The media object includes a memory buffer containing video data to be processed. In some embodiments, all media pipeline states must be valid before issuing media object commands 2442. Once the pipeline state is configured and media object commands 2442 are queued, media pipeline 2424 is triggered via an execute command 2444 or an equivalent execution event (e.g., a register write). The output from media pipeline 2424 can then be post-processed by operations provided by 3D pipeline 2422 or media pipeline 2424. In some embodiments, GPGPU operations are configured and executed in a manner similar to media operations.

[0367] Graphics software architecture

[0368] Fig.25 An exemplary graphics software architecture of a data processing system 2500 according to some embodiments is shown. In some embodiments, the software architecture includes a 3D graphics application 2510, an operating system 2520, and at least one processor 2530. In some embodiments, processor 2530 includes a graphics processor 2532 and one or more general purpose processor cores 2534. Graphics application 2510 and operating system 2520 are each executed in a system memory 2550 of the data processing system.

[0369] In some embodiments, the 3D graphics application 2510 includes one or more shader programs that include shader instructions 2512. The shader language instructions may be in a high-level shader language, such as High-Level Shader Language (HLSL) or OpenGL Shader Language (GLSL). The application also includes executable instructions 2514 in a machine language suitable for execution by a general purpose processor core 2534. The application also includes geometric objects 2516 defined by vertex data.

[0370] In some embodiments, operating system 2520 is from Microsoft Corporation Operating system, proprietary UNIX-like operating system using a variant of the Linux kernel, or an open source UNIX-like operating system. When the Direct3D API is in use, the operating system 2520 uses a front-end shader compiler 2524 to compile any shader instructions 2512 in HLSL into a low-level shader language. The compilation can be a just-in-time (JIT) compilation, or the application can execute shader pre-compilation. In some embodiments, during the compilation of the 3D graphics application 2510, the high-order shader is compiled into a low-order shader.

[0371] In some embodiments, the user mode graphics driver 2526 includes a backend shader compiler 2527 that is used to convert shader instructions 2512 into hardware specific representations. When the OpenGL API is in use, the shader instructions 2512 in the GLSL high-level language are passed to the user mode graphics driver 2526 for compilation. In some embodiments, the user mode graphics driver 2526 uses operating system kernel mode functions 2528 to communicate with the kernel mode graphics driver 2529. In some embodiments, the kernel mode graphics driver 2529 communicates with the graphics processor 2532 to dispatch commands and instructions.

[0372] IP core implementation

[0373] One or more aspects of at least one embodiment may be implemented by representative code stored on a machine-readable medium, which represents and / or defines logic within an integrated circuit (e.g., a processor). For example, a machine-readable medium may include instructions representing the various logics within a processor. When read by a machine, the instructions may cause the machine to manufacture logic for performing the techniques described herein. Such representations (referred to as "IP cores") are reusable units of logic for an integrated circuit, which may be stored on a tangible, machine-readable medium as a hardware model describing the structure of the integrated circuit. The hardware model may be supplied to each consumer or manufacturing facility that loads the hardware model on a manufacturing machine that manufactures the integrated circuit. The integrated circuit may be manufactured so that the circuit performs the operations described in association with any of the embodiments described herein.

[0374] Fig.26 2600 is a block diagram showing an IP core development system according to an embodiment, and the IP core development system can be used to manufacture an integrated circuit to perform operations. The IP core development system 2600 can be used to generate a modular, reusable design that can be incorporated into a larger design or used to build an entire integrated circuit (e.g., a SOC integrated circuit). The design facility 2630 can use a high-level programming language (e.g., C / C++) to generate a software simulation 2610 for the IP core design. The software simulation 2610 can be used to design, test and verify the behavior of the IP core. Then the register transfer level (RTL) design can be created or synthesized by the simulation model 2600. The RTL design 2615 is an abstraction of the behavior of an integrated circuit (including associated logic executed using the modeled digital signals) that models the flow of digital signals between hardware registers. In addition to the RTL design 2615, a lower level design at a logic level or transistor level can also be created, designed or synthesized. Thus, the specific details of the initial design and simulation can change.

[0375] The RTL design 2615 or equivalent may be further synthesized by the design facility into a hardware model 2620, which may be in a hardware description language (HDL) or some other representation of physical design data. The HDL may be further simulated or tested to verify the IP core design. The IP core design may be stored using a non-volatile memory 2640 (e.g., a hard disk, flash memory, or any non-volatile storage medium) for delivery to a third-party manufacturing facility 2665. Alternatively, the IP core design may be transmitted (e.g., via the Internet) via a wired connection 2650 or a wireless connection 2660. The manufacturing facility 2665 may then manufacture an integrated circuit based at least in part on the IP core design. The manufactured integrated circuit may be configured to perform operations according to at least one embodiment described herein.

[0376] Fig. 27 2700, which can be manufactured using one or more IP cores. The exemplary integrated circuit includes one or more application processors 2705 (e.g., CPUs), at least one graphics processor 2710, and may additionally include an image processor 2715 and / or a video processor 2720, any of which may be modular IP cores from the same or multiple different design facilities. The integrated circuit includes peripheral or bus logic, including a USB controller 2725, a UART controller 2730, an SPI / SDIO controller 2735, an I 2 S / I 2 The integrated circuit may include a display device 2745 coupled to one or more of a high-definition multimedia interface (HDMI) controller 2750 and a mobile industry processor interface (MIPI) display interface 2755. Storage may be provided by a flash memory subsystem 2760 (including flash memory and a flash memory controller). A memory interface may be provided via a memory controller 2765 for accessing SDRAM or SRAM memory devices. Some integrated circuits additionally include an embedded security engine 2770.

[0377] Additionally, other logic and circuitry may be included in the processor of integrated circuit 2700 , including additional graphics processors / cores, peripheral interface controllers, or general purpose processor cores.

[0378] Advantageously, any of the above-described systems, processors, graphics processors, devices, and / or methods may be integrated with or configured with any of the various embodiments described herein (e.g., or portions thereof), including, for example, those described in the following additional notes and examples.

[0379] Additional Notes and Examples

[0380] Example 1 may include a graphics device comprising: a processor; a memory communicatively coupled to the processor; and a collaboration engine communicatively coupled to the processor for identifying shared graphics components between two or more users in an environment; and sharing the shared graphics components with the two or more users in the environment.

[0381] Example 2 may include a device as described in Example 1, wherein the collaboration engine further includes a centralized sharer, the centralized sharer being used for: a broadcaster for broadcasting the shared graphic component to all of the two or more users; and a distributor for individually distributing a separate graphic component to one of the two or more users.

[0382] Example 3 may include the apparatus of Example 2, wherein the centralized sharer is further configured to: split the workload of the shared graphics component based on a target virtual reality device.

[0383] Example 4 may include a device as described in Example 1, wherein the collaboration engine further includes a depth sharer, the depth sharer being used to: collect depth information from a source independent of a first user among the two or more users; and share the depth information with the first user.

[0384] Example 5 may include the device of Example 4, wherein the depth sharer is further used to: collect visibility information from the independent source outside the field of view of the first user; and share the visibility information with the first user.

[0385] Example 6 may include the apparatus of Example 1, wherein the collaboration engine further comprises a shared preprocessor configured to: precompute information related to the shared graphics component; and share the precomputed information with the two or more users.

[0386] Example 7 may include the apparatus of Example 6, wherein the pre-computed information includes one or more of geometric information, primitive information, and physical information.

[0387] Example 8 may include the apparatus of Example 1, wherein the collaboration engine further comprises a multi-port graphics subsystem to support a different user on each port of the multi-port graphics subsystem.

[0388] Example 9 may include the device of Example 8, wherein the multi-port graphics subsystem is further configured to: support a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem; support the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; and share graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

[0389] Example 10 may include a device as described in Example 1, wherein the collaboration engine further includes a decoding sharer, which is used to: identify an overlapping area of ​​a shared scene between a first view area of ​​a first user and a second view area of ​​a second user; decode the overlapping area; and share the decoded overlapping area with both the first user and the second user.

[0390] Example 11 may include the apparatus of Example 10, wherein the decode sharer is further configured to prioritize the decodes based on the overlap region.

[0391] Example 12 may include a method of graphical collaboration, the method comprising: identifying a shared graphical component between two or more users in an environment; and sharing the shared graphical component with the two or more users in the environment.

[0392] Example 13 may include the method of Example 12, further comprising: broadcasting the shared graphics component to all of the two or more users; and individually allocating an individual graphics component to one of the two or more users.

[0393] Example 14 may include the method of Example 13, further comprising: splitting the workload of the shared graphics component based on a target virtual reality device.

[0394] Example 15 may include the method of Example 12, further comprising: collecting depth information from a source independent of a first user of the two or more users; and sharing the depth information with the first user.

[0395] Example 16 may include the method of Example 15, further comprising: collecting visibility information from the independent source outside the field of view of the first user; and sharing the visibility information with the first user.

[0396] Example 17 may include the method of Example 12, further comprising: pre-calculating information related to the shared graphics component; and sharing the pre-calculated information with the two or more users.

[0397] Example 18 may include the method of Example 17, wherein the precomputed information includes one or more of geometric information, primitive information, and physical information.

[0398] Example 19 may include the method of Example 12, further comprising supporting a different user on each port of the multi-port graphics subsystem.

[0399] Example 20 may include the method of Example 19, further comprising: supporting a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem; supporting the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; and sharing graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

[0400] Example 21 may include the method as described in Example 12, further comprising: identifying an overlapping area of ​​a shared scene between a first view area of ​​a first user and a second view area of ​​a second user; decoding the overlapping area; and sharing the decoded overlapping area with both the first user and the second user.

[0401] Example 22 may include the method of Example 21, further comprising: prioritizing the decoding based on the overlapping region.

[0402] Example 23 may include at least one computer-readable medium comprising a set of instructions that, when executed by a computing device, cause the computing device to: identify a shared graphic component between two or more users in an environment; and share the shared graphic component with the two or more users in the environment.

[0403] Example 24 may include at least one computer-readable medium as described in Example 23, comprising another set of instructions that, when executed by a computing device, cause the computing device to: broadcast the shared graphics component to all of the two or more users; and individually allocate a separate graphics component to one of the two or more users.

[0404] Example 25 may include at least one computer-readable medium as described in Example 24, comprising another set of instructions that, when executed by a computing device, cause the computing device to: split the workload of the shared graphics component based on a target virtual reality device.

[0405] Example 26 may include at least one computer-readable medium as described in Example 23, comprising another set of instructions that, when executed by a computing device, cause the computing device to: collect depth information from a source independent of a first user of the two or more users; and share the depth information with the first user.

[0406] Example 27 may include at least one computer-readable medium as described in Example 26, comprising another set of instructions that, when executed by a computing device, cause the computing device to: collect visibility information from the independent source outside the field of view of the first user; and share the visibility information with the first user.

[0407] Example 28 may include at least one computer-readable medium as described in Example 23, comprising another set of instructions that, when executed by a computing device, cause the computing device to: precompute information related to the shared graphics component; and share the precomputed information with the two or more users.

[0408] Example 29 may include at least one computer-readable medium as described in Example 28, wherein the pre-computed information includes one or more of geometric information, primitive information, and physical information.

[0409] Example 30 may include the at least one computer readable medium of Example 23, comprising another set of instructions that, when executed by a computing device, cause the computing device to: support a different user on each port of a multi-port graphics subsystem.

[0410] Example 31 may include at least one computer-readable medium as in Example 30, comprising another set of instructions that, when executed by a computing device, cause the computing device to: support a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem; support the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; and share graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

[0411] Example 32 may include at least one computer-readable medium as described in Example 23, comprising another set of instructions that, when executed by a computing device, cause the computing device to: identify an overlap area of ​​a shared scene between a first view area of ​​a first user and a second view area of ​​a second user; decode the overlap area; and share the decoded overlap area with both the first user and the second user.

[0412] Example 33 may include the at least one computer readable medium of Example 32, comprising another set of instructions that, when executed by a computing device, cause the computing device to: prioritize the decoding based on the overlap region.

[0413] Example 34 may include a graphics device comprising: means for identifying a shared graphics component between two or more users in an environment; and means for sharing the shared graphics component with the two or more users in the environment.

[0414] Example 35 may include the apparatus of Example 34, further comprising: means for broadcasting the shared graphic component to all of the two or more users; and means for individually allocating an individual graphic component to one of the two or more users.

[0415] Example 36 may include the apparatus of Example 35, further comprising: means for splitting the workload of the shared graphics component based on a target virtual reality device.

[0416] Example 37 may include the apparatus of Example 34, further comprising: means for collecting depth information from a source independent of a first user of the two or more users; and means for sharing the depth information with the first user.

[0417] Example 38 may include the apparatus of Example 37, further comprising: means for collecting visibility information from the independent source outside the field of view of the first user; and means for sharing the visibility information with the first user.

[0418] Example 39 may include the apparatus of Example 34, further comprising: means for pre-calculating information related to the shared graphics component; and means for sharing the pre-calculated information with the two or more users.

[0419] Example 40 may include the apparatus of Example 39, wherein the precomputed information comprises one or more of geometric information, primitive information, and physical information.

[0420] Example 41 may include the apparatus of Example 34, further comprising: means for supporting a different user on each port of the multi-port graphics subsystem.

[0421] Example 42 may include the apparatus of Example 41, further comprising: means for supporting a left-eye display and a right-eye display of a first virtual reality device when only the first virtual reality device is connected to the multi-port graphics subsystem; means for supporting the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; and means for sharing graphics primitives between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

[0422] Example 43 may include an apparatus as described in Example 34, further comprising: a device for identifying an overlapping area of ​​a shared scene between a first view area of ​​a first user and a second view area of ​​a second user; a device for decoding the overlapping area; and a device for sharing the decoded overlapping area with both the first user and the second user.

[0423] Example 44 may include the apparatus of Example 43, further comprising: means for prioritizing the decoding based on the overlapping region.

[0424] Example 45 may include an image device comprising: a processor; a memory communicatively coupled to the processor; a collaboration engine communicatively coupled to the processor to receive a shared graphics component; and a synthesizer communicatively coupled to the processor to merge the shared graphics component with a separate graphics component.

[0425] Example 46 may include a device as described in Example 45, further comprising: a wearable housing to be worn by a user; and a display communicatively coupled to the processor, wherein the display, the processor, the memory, the collaboration interface, and the synthesizer are all supported by the wearable housing.

[0426] Example 47 may include the apparatus of Example 45, wherein the collaboration interface is further for receiving broadcast information including the shared graphics component.

[0427] Example 48 may include the apparatus of Example 45, wherein the shared graphics components include one or more of shared depth information, shared geometry information, and shared physics information.

[0428] Example 49 may include the apparatus of Example 45, further comprising: a multi-port graphics subsystem for supporting a different user on each port.

[0429] Example 50 may include the apparatus of Example 45, wherein the shared graphics component includes 360 video content.

[0430] Example 51 may include a method of graphics collaboration, the method comprising: receiving a shared graphics component; and merging the shared graphics component with a separate graphics component.

[0431] Example 52 may include the method of Example 51, further comprising: providing a wearable housing to be worn by a user; and using the wearable housing to support a display, a processor, a memory, a collaboration interface, and a synthesizer.

[0432] Example 53 may include the method of Example 51, further comprising: receiving broadcast information including the shared graphics component.

[0433] Example 54 may include the method of Example 51, wherein the shared graphics components include one or more of shared depth information, shared geometry information, and shared physics information.

[0434] Example 55 may include the method of Example 51, further comprising supporting a different user on each port of the multi-port graphics subsystem.

[0435] Example 56 may include the method of Example 51, wherein the shared graphics component includes 360 video content.

[0436] Example 57 may include at least one computer-readable medium comprising a set of instructions that, when executed by a computing device, cause the computing device to: receive a shared graphics component; and merge the shared graphics component with a separate graphics component.

[0437] Example 58 may include at least one computer-readable medium as described in Example 57, comprising another set of instructions that, when executed by a computing device, cause the computing device to: receive broadcast information including the shared graphics component.

[0438] Example 59 may include at least one computer-readable medium as described in Example 57, wherein the shared graphics components include one or more of shared depth information, shared geometry information, and shared physics information.

[0439] Example 60 may include the at least one computer readable medium of Example 57, comprising another set of instructions that, when executed by a computing device, cause the computing device to: support a different user on each port of a multi-port graphics subsystem.

[0440] Example 61 may include at least one computer-readable medium as described in Example 57, wherein the shared graphics component includes 360 video content.

[0441] Example 62 may include a graphics device comprising: means for receiving a shared graphics component; and means for merging the shared graphics component with a separate graphics component.

[0442] Example 63 may include an apparatus as described in Example 62, further comprising: means for providing a wearable housing to be worn by a user; and means for using the wearable housing to support a display, a processor, a memory, a collaborative interface, and a synthesizer.

[0443] Example 64 may include the apparatus of Example 62, further comprising: means for receiving broadcast information including the shared graphics component.

[0444] Example 65 may include the apparatus of Example 62, wherein the shared graphics components include one or more of shared depth information, shared geometry information, and shared physical information.

[0445] Example 66 may include the apparatus of Example 62, further comprising: means for supporting a different user on each port of the multi-port graphics subsystem.

[0446] Example 67 may include the apparatus of Example 62, wherein the shared graphics component comprises 360 video content.

[0447] Embodiments are applicable to all types of semiconductor integrated circuit ("IC") chips. Examples of these IC chips include, but are not limited to, processors, controllers, chipset components, programmable logic arrays (PLA), memory chips, network chips, systems on chips (SoC), SSD / NAND controller ASICs, etc. In addition, in some of the drawings, signal conductor lines are represented by lines. Some lines may be different to indicate more constituent signal paths, with digital markings to indicate the numbering of constituent signal paths and / or arrows at one or more ends to indicate the main information flow direction. However, this should not be interpreted in a restrictive manner. Instead, such additional details may be used in conjunction with one or more exemplary embodiments to help make it easier to understand the circuit. Any signal line represented, whether or not there is additional information, may actually include one or more signals that can travel in multiple directions, and may be implemented using any appropriate type of signal scheme, such as digital or analog lines implemented using differential pairs, fiber optic lines, and / or single-ended lines.

[0448] Example sizes / models / values / ranges may have been given, although embodiments are not limited thereto. As manufacturing techniques (e.g., photolithography) mature over time, it is expected that devices of smaller sizes can be manufactured. In addition, in order to simplify illustration and discussion and in order not to make some aspects of the embodiments unclear, known power / ground connections to IC chips and other components may or may not be shown in the figure. In addition, the arrangement may be shown in the form of a block diagram to avoid blurring the embodiments, and also in view of the fact that the details of the implementation methods of such block diagram arrangements are highly dependent on the platform in which the embodiments are implemented, that is, such details should be completely within the horizon of those skilled in the art. In the case of elaborating specific details (e.g., circuits) to describe example embodiments, it should be apparent to those skilled in the art that embodiments can be practiced without these specific details or with variations of these specific details. The description is therefore considered to be illustrative rather than restrictive.

[0449] The term "coupled" may be used herein to refer to any type of direct or indirect relationship between the components in question, and may apply to electronic, mechanical, fluid, optical, electromagnetic, electromechanical or other connections. In addition, the terms "first", "second", etc. may be used herein merely to facilitate discussion, and do not carry any specific temporal or temporal significance, unless otherwise specified. Moreover, the indefinite article "a" or "an" is understood to carry the meaning of "one or more" or "at least one".

[0450] As used in this application and in the claims, a list of items described by the term "one or more" may mean any combination of the listed items. For example, the phrase "one or more of A, B, and C" may mean A, B, C; A and B; A and C; B and C; or A, B, and C.

[0451] The embodiments have been described above with reference to specific embodiments. However, it will be appreciated by those skilled in the art that various modifications and changes may be made thereto without departing from the broader spirit and scope of the embodiments as set forth in the appended claims. The foregoing description and drawings are therefore considered to be illustrative rather than restrictive.

Claims

1. A graphics device, include: processor; a memory communicatively coupled to the processor; as well as a collaboration engine, communicatively coupled to the processor, for: determining a viewpoint difference between a first viewpoint and a second viewpoint, wherein the first viewpoint is associated with a first user of two or more users and the second viewpoint is associated with a second user of the two or more users; In response to determining that the viewpoint difference is below a threshold, identifying a portion of a displayable object to be used as a background, wherein the displayable object is for rendering in a same orientation and at a same location for the first user and the second user; generating the background; and The context is shared with the first user and the second user.

2. The device as claimed in claim 1, in, The collaboration engine further includes a centralized sharer, the centralized sharer being configured to: The workload of the shared graphics component is split based on a target virtual reality device.

3. The device as claimed in claim 1, in, The collaboration engine further comprises a depth sharer, the depth sharer being configured to: collecting depth information from an independent source independent of the first user; and The depth information is shared with the first user.

4. The device as claimed in claim 3, in, The depth sharer is further used to: collecting visibility information from the independent source outside of the first user's field of view; and The visibility information is shared with the first user.

5. The device as claimed in claim 1, in, The collaboration engine further comprises a shared preprocessor, the shared preprocessor being configured to: pre-calculating information related to the shared graphics component; and The precomputed information is shared with the two or more users.

6. The device as claimed in claim 5, in, The pre-calculated information includes one or more of geometric information, primitive information, and physical information.

7. The device as claimed in claim 1, in, The collaboration engine further includes a multi-port graphics subsystem, the multi-port graphics subsystem being configured to: A different user is supported on each port of the multi-port graphics subsystem.

8. The device as claimed in claim 7, in, The multi-port graphics subsystem is further configured to: When only a first virtual reality device is connected to the multi-port graphics subsystem, supporting a left-eye display and a right-eye display of the first virtual reality device; supporting the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; and Graphics primitives are shared between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

9. The device as claimed in claim 1, in, The collaboration engine further includes a decoding sharer, the decoding sharer is used to: identifying an overlapping area of ​​a shared scene between a first view area of ​​the first user and a second view area of ​​the second user; decoding the overlap region; and The decoded overlap region is shared with both the first user and the second user.

10. The device according to claim 9, in, The decoding sharer is further used for: The decoding is prioritized based on the overlap region.

11. A method for graphic collaboration, the method include: determining a viewpoint difference between a first viewpoint and a second viewpoint, wherein the first viewpoint is associated with a first user of two or more users and the second viewpoint is associated with a second user of the two or more users; In response to determining that the viewpoint difference is below a threshold, identifying a displayable object to be part of a background, wherein the displayable object is for rendering at a same orientation and at a same location for the first user and the second user; generating the background; and The context is shared with the first user and the second user.

12. The method of claim 11, further comprising: include: The workload of the shared graphics component is split based on a target virtual reality device.

13. The method of claim 11, further comprising: include: collecting depth information from an independent source independent of the first user; as well as The depth information is shared with the first user.

14. The method of claim 13, further comprising: include: collecting visibility information from the independent source outside of the first user's field of view; as well as The visibility information is shared with the first user.

15. The method of claim 11, further comprising: include: pre-calculating information related to the shared graphics component; as well as The precomputed information is shared with the two or more users.

16. The method of claim 15, in, The pre-calculated information includes one or more of geometric information, primitive information, and physical information.

17. The method of claim 11, further comprising: include: Supports different users on each port of a multi-port graphics subsystem.

18. The method of claim 17, further comprising: include: When only a first virtual reality device is connected to the multi-port graphics subsystem, supporting a left-eye display and a right-eye display of the first virtual reality device; supporting the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem; as well as Graphics primitives are shared between the first virtual reality device and the second virtual reality device when both the first virtual reality device and the second virtual reality device are connected to the multi-port graphics subsystem.

19. The method of claim 11, further comprising: include: identifying an overlapping area of ​​a shared scene between a first view area of ​​the first user and a second view area of ​​the second user; Decoding the overlapping area; as well as The decoded overlap region is shared with both the first user and the second user.

20. The method of claim 19, further comprising: include: The decoding is prioritized based on the overlap region.

21. A graphics device, include: Means for determining a viewpoint difference between a first viewpoint and a second viewpoint, wherein the first viewpoint is associated with a first user of two or more users and the second viewpoint is associated with a second user of the two or more users; means for identifying a portion of a displayable object to be a background in response to determining that the viewpoint difference is below a threshold, wherein the displayable object is for rendering at the same orientation and at the same location for the first user and the second user; means for broadcasting the background to all of the two or more users; and Means for sharing the context with the first user and the second user.

22. The device of claim 21, further comprising: include: Means for splitting the workload of the shared graphics component based on a target virtual reality device.

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