129 results about "Display memory" patented technology

The invention discloses a CFD (computational fluid dynamics) boundary processing acceleration method based on GPU (graphics processing unit) parallelism, and belongs to the technical field of fluid mechanics related calculation. The problem that in the prior art, a traditional CFD boundary processing acceleration method is low in calculation efficiency is solved. The method comprises the following steps: generating a computational grid required for simulating a flow field, and reading grid information and boundary condition information of computational simulation; initializing a flow field according to the calculation parameters, copying flow field data and flow field boundary information from a main memory to a video memory, establishing a boundary pointer array in the video memory, and instantiating a boundary pointed by each pointer; according to the boundary pointer array, the flow field data and the flow field boundary information, time step cycle calculation is carried out by utilizing a GPU, and physical quantity updating of a boundary virtual unit corresponding to the thread is realized; and after time step cycle calculation convergence, video memory flow field data are copied to a main memory, and flow field simulation calculation is completed. The method effectively improves the calculation efficiency, and can be applied to CFD boundary processing.

The invention relates to a multi-node resource scheduling method for a cloud three-dimensional modeling task, and relates to the technical field of cloud computing resource scheduling, and the method comprises the specific steps: analyzing a three-dimensional modeling task log stream in real time, determining a current modeling stage through a regular matching key operation instruction, and according to a label of the current stage, carrying out the multi-node resource scheduling of the cloud three-dimensional modeling task. The method comprises the following steps: extracting a GPU / CPU matching rule and a video memory capacity requirement of a corresponding stage from a preset resource configuration template library, dynamically calculating a block parameter N of a to-be-reconstructed grid based on the video memory capacity requirement, and dividing the to-be-reconstructed grid into N * N * N sub-blocks according to spatial positions; by analyzing the three-dimensional modeling task log stream in real time and utilizing the regular matching key operation instruction, the current modeling stage can be accurately recognized, and then the GPU / CPU matching rule and the video memory capacity requirement of the corresponding stage are extracted from the preset resource configuration template library.

According to the method, PCIe extended storage equipment is identified by responding to a system starting signal, and initialization and address mapping control logic is executed to construct a first address space addressable by a GPU (Graphics Processing Unit); then, loading model data according to an AI task instruction, and dynamically dividing hot, warm and cold multi-level data popularity levels by monitoring memory access frequency; a migration data block is generated based on the popularity level, a migration data flow is organized and verified through priority scheduling logic, and intelligent data scheduling between extended storage and a GPU video memory is achieved; finally, the resources are released after the task is completed. Therefore, dynamic expansion of the physical video memory capacity is effectively achieved, large-scale AI model localization training is met, dependence on a high-end GPU chip is remarkably reduced, and data safety and system economy are improved.

The embodiment of the invention provides a video memory control method, device, equipment and system and a computer storage medium. The method comprises the steps that in response to an obtained drive upgrading request of an image processing unit (GPU), a before-upgrading page table corresponding to the GPU is obtained, and the before-upgrading page table comprises a mapping relation between a physical address and a virtual address of a GPU video memory; determining a data cleaning queue corresponding to the GPU, wherein the data cleaning queue is used for performing global cleaning on data in a GPU video memory; under the condition that the data cleaning queue is locked, driving upgrading operation is carried out on the GPU based on the driving upgrading request, an upgraded page table corresponding to the GPU is obtained, and the upgraded page table comprises a mapping relation between a physical address and a virtual address of a GPU video memory; and regulating and controlling data in the GPU video memory based on the pre-upgrading page table and the post-upgrading page table. In the embodiment of the invention, the driver upgrading operation of the GPU can be realized without operations such as video memory backup, shutdown, restart and the like.

Content-addressable memory-in-display (CAMiD) electronic displays and circuitry are provided. An electronic display may include a pixel active array and content-addressable control cells to control display pixels of the pixel active array using control signals propagated to the pixel active array on column lines by column driver circuits of the content-addressable control cells.

The invention discloses a big language model dialogue system for Token-level resident memory and a use method. The big language model dialogue system comprises an inference engine module, a big language model module, an independent memory model module and an external storage module, relates to the technical field of big language model memory enhancement, after a current dialogue Token sequence is received, whether historical dialogue information is needed or not is judged through a big language model module, and if yes, the historical dialogue information is called from an external storage module through an independent memory model module, so that information displayed by finally responding to the Token sequence is more complete, and user experience is improved. The problems that a model cannot completely retain and utilize long-distance historical information, so that questions cannot be answered and information is forgotten are solved; an external storage module is arranged, and model parameters of an independent memory model module and Token-level data of all historical conversations are resided through a memory mapping technology; and zero occupation of the GPU video memory is realized.

The invention relates to the technical field of computer graphics, and particularly discloses a three-dimensional intelligent visualization method and device for multi-source data loading, a medium and equipment.The method comprises the steps that an oblique photography model is loaded and dynamically adjusted, and an oblique photography live-action base is constructed; generating semantic 3D tiles data on the basis of the base; identifying a key entity object, carrying out lightweight processing on a high-precision GLB / GLTF model of the key entity object, and dynamically implanting the high-precision GLB / GLTF model into a scene; performing dynamic analysis and spatial superposition on the KML data associated with the key object, and constructing a multi-level three-dimensional scene information system from entity annotation to macroscopic annotation; dynamically coupling the KML elements with terrain elevation data to form a high-precision digital elevation base supporting visualization; based on a video memory dynamic partitioning mechanism, optimized resource scheduling is performed on a substrate, and adaptive balance of terrain complexity and system load is realized. According to the invention, the precision and efficiency of multi-source heterogeneous data fusion and the system stability can be improved.

The invention relates to an ultra-high-definition image restoration method, device and equipment based on clustering center feature scanning. The method comprises the steps that a clustering center scanning unit and a space-channel feature modulator are constructed, the clustering center scanning unit constructs a plurality of center features through a feature aggregation stage sparse sampling input feature map, a cosine similarity matrix of pixels and the center features is calculated, similar pixels are screened through an activation function and aggregated to generate clustering core features, and the clustering core features are clustered through the space-channel feature modulator; the similarity matrix is utilized to establish association mapping of core and non-core features through a fractional diffusion stage, global modeling weight is transmitted, a space-channel feature modulator extracts global features and texture detail features through parallel attention branches, the two modules are fused based on an asymmetric encoder-decoder architecture, and the texture detail features are obtained. According to the method, an ultra-high-definition image restoration network is constructed, low-quality ultra-high-definition images are restored after training, high-quality images are output, and the problems of video memory bottleneck and detail blurring in the prior art can be effectively solved.

A method for sharing a distributed video memory across process groups and a computing device, the method comprising: in response to receiving a recovery instruction from an upper application, a first process in a plurality of processes traverses metadata of each virtual address in a first metadata table thereof, mapping a first physical address to each of the plurality of first virtual addresses of the local mapping type, wherein the recovery indication is sent by the upper application after determining that the second process group releases the video memories of the plurality of GPUs; under the condition that metadata of a target virtual address in the plurality of first virtual addresses comprises a reference relationship between a second virtual address in a second process and the target virtual address, the first process provides a first export value corresponding to the second virtual address and a target physical address to the second process, the target physical address is used for exporting the video memory from the second process, and the target virtual address and the target physical address are mapped.

This application discloses a method and apparatus for managing video memory blocks, belonging to the field of data processing technology. The method includes: acquiring the occupancy status and access activity curves of video memory blocks within multiple consecutive address segments; for each consecutive address segment, performing frequency domain transformation and encoding based on the occupancy status and access activity curves of the video memory blocks within the segment to generate a video memory convolution spectrum characterizing the fragmentation degree and temporal access activity of that segment of video memory; determining candidate migration regions based on the video memory convolution spectra of each consecutive address segment; determining the differential tensors of candidate video memory blocks within the candidate migration regions; performing a comprehensive evaluation based on the differential tensors of all candidate video memory blocks under preset bandwidth and quality of service constraints to generate a video memory migration plan; and calling the underlying interface to execute the batch migration of candidate video memory blocks according to the video memory migration plan.

The application provides a Gaussian ball clustering method for three-dimensional reconstruction of a highway traffic accident site, comprising the following steps: S1, collecting multi-view images of the accident site, solving camera parameters and initializing a three-dimensional Gaussian ball scene; S2, constructing a rendering training loop based on the initialized three-dimensional Gaussian ball scene, and adaptively adjusting the Gaussian ball density through cloning or splitting operations; S3, extracting the spatial and color features of the three-dimensional Gaussian ball, and constructing a multi-modal physical feature set; S4, calculating an adaptive discrete step length based on the multi-modal physical feature set, and mapping the continuous features into discrete coordinates; S5, generating a multi-modal hash index based on the discrete coordinates, and realizing continuous rearrangement of the same type of Gaussian ball in the display memory through GPU parallel sorting; S6, performing physical conservation formula parameter aggregation on the same type of Gaussian ball continuously stored in the display memory, releasing redundant display memory and simplifying the three-dimensional Gaussian ball set; and S7, completing all training iterations, and exporting the final simplified three-dimensional Gaussian ball set into a general PLY format file.

The application provides a perspective image reconstruction method and a readable storage medium. The perspective image reconstruction method comprises the following steps: setting a plurality of calculation nodes in series based on a perspective image reconstruction process, and the plurality of calculation nodes work in parallel; inputting a view data to a first calculation node of the plurality of calculation nodes in a time period; and outputting a perspective image by a last calculation node of the plurality of calculation nodes. In this way, each calculation node operates independently and does not interfere with each other, and each calculation node processes one view data at a time, the data amount involved in each execution is small, the scheduling is convenient, the view data can be discarded immediately after being used, and the consumption of memory and display memory is reduced. Thus, the problem that the reconstruction method in the prior art has a long delay, a low refresh frequency and cannot meet the real-time requirement of the perspective image in special occasions is solved.

The application discloses a liquid crystal display module, a liquid crystal display control method and device, and applies to the field of display control, and comprises the following steps: obtaining to-be-displayed content of a liquid crystal display screen; filling a dot matrix image corresponding to the to-be-displayed content in a pre-allocated virtual display memory; and performing a full-screen refreshing operation on the liquid crystal display screen according to the dot matrix image, so as to present the to-be-displayed content on a display area of the liquid crystal display screen. Through the application, the problem of complex coordinate calculation work and display area flickering caused by cross-page display of the liquid crystal display screen is at least solved to a certain extent.

A multi-screen interaction method, device, system and storage medium solve the problem that private customization cannot be realized and display efficiency is low when multi-screen display in the multi-screen interaction process in the prior art. The multi-screen interaction method is used for a multi-screen interaction system including a display chip, a display memory, a main display screen and a secondary display screen. The display memory includes a plurality of layer display memory areas, a main display memory area and a virtual display memory area. The plurality of layer display memory areas respectively store graphical data of a plurality of application programs. The main display memory area stores synthesis data of the plurality of application programs. The plurality of application programs include a target application program. The multi-screen interaction method includes: determining a secondary display screen selected by a user and screen projection content based on a screen projection operation of the user; when the screen projection content is the target application program, storing graphical data of the target application program in the virtual display memory area; and sending the graphical data in the virtual display memory area and the synthesis data in the main display memory area to the secondary display screen and the main display screen respectively for display.

The application discloses an LCD-TFT controller, and relates to the technical field of display control, which mainly comprises a direct memory access module (DMA), two-layer image processing units, a blending module (Blend) and a dithering module (Dither). The image processing unit of each layer comprises a 2x1 selector, a color look-up table (CLUT), a pixel format converter (PFC) and a matte color changing module. The PFC further comprises a YUV2RGB module, which is used for converting YUV format image source data into RGB format. The matte color changing module is used for selectively realizing the functions of matte and color changing under the control of an enabling signal and outputting. Compared with the traditional LCD-TFT controller, the application supports YUV color format, realizes the functions of automatically identifying color ranges and changing colors, and reduces the demand of an MCU on the size of a display memory.

The present disclosure provides an extended video memory-based model training method, a model inference method, an apparatus, a device, a medium and a product, relating to the technical field of storage devices. The extended video memory-based model training method comprises: sending a first DSM instruction to an SSD controller, and performing multiple rounds of iterative training by a GPU. Each round of iterative training comprises multiple processing stages. The processing stages comprise: the SSD controller loading data units before calculation corresponding to hierarchical identifiers to the GPU, and the GPU calculating calculation units based on the data units. The first DSM instruction marks the priority of the calculation units. The GPU unloads the calculation units to the SSD. The SSD controller unloads the calculation units of high priority to SLC and unloads the calculation units of low priority to QLC. Through the technical solution of the present disclosure, the access delay of high-sensitive data is reduced without increasing the hardware cost, and the invalid erasing and writing of SLC is reduced to prolong the service life of the SSD.

The invention discloses a method for changing the capacity of a video memory based on a printed circuit board, which can be used in the field of electronic circuits, and comprises the following steps: firstly, acquiring a first pin definition file of an original video memory chip and a second pin definition file of a target video memory chip on the printed circuit board; then, comparing the first pin definition file with the second pin definition file, and determining incompatible pins; then, based on a preset path planning rule, determining a fly line path corresponding to each incompatible pin; the path planning rule at least comprises path length control, interference source distance control and non-intersection of a plurality of fly lines; and finally, based on the fly line path, welding the target video memory chip to the printed circuit board of which the original video memory chip is removed. Therefore, redesign, proofing and PCB manufacturing are not needed, capacity expansion can be realized by using existing hardware resources, the time cost and the economic cost of video memory capacity change are greatly reduced, and the problems of long period and large investment of a traditional scheme are solved.

The invention discloses a model loading reasoning method and device, a medium and a product, which are applied to a financial science and technology scene, and the method comprises the following steps: registering a model related file in a model memory through a controller, and initializing the model related file; segmenting a model related file into a specified size through a model memory, establishing storage mapping of a video memory and a rapid memory, and feeding back model segmentation information to a controller; state monitoring information is obtained in real time through the state monitoring assembly and fed back to the controller; and when the gateway receives a model reasoning request, performing model loading reasoning through the controller according to the state monitoring information. Model related files are segmented through the model memory, and storage mapping is established, so that flexible segmentation and rapid calling of the model can be realized, and support is provided for scheduling; by monitoring state information, the controller comprehensively masters the system state to assist in decision making; and after the gateway receives the request, the controller performs model loading reasoning according to the request, so that resources can be flexibly scheduled, and the response speed, the accuracy and the resource utilization rate are improved.

The application relates to an OpenGL multi-class object uniform drawing method based on VBO internal coding, which comprises the following steps: constructing a mixed data structure containing vertex coordinates, color components, texture coordinates and object type marks, and storing the mixed data structure in the memory of a VBO in an interlaced arrangement; defining a uniform vertex shader and a fragment shader; judging whether texture mapping is needed according to the object type marks during a rendering process; and deleting the VBO object and the shader program after the rendering is completed, and releasing the display memory and the memory resources. The application links map elements with different rendering logics, realizes the uniform drawing of heterogeneous objects under a single pipeline, fully utilizes the parallel processing capacity of a GPU, avoids frequent switching of the shader, effectively saves the communication bandwidth between a CPU and the GPU, simplifies the development difficulty of multi-map element mixed rendering in a complex scene, and facilitates the horizontal expansion of a system in large-scale geographic information visualization.

Embodiments of the present application provide a display memory control method, device, equipment, system and computer storage medium. The method comprises: in response to an obtained driving upgrade request of a graphics processing unit (GPU), obtaining a pre-upgrade page table corresponding to the GPU, the pre-upgrade page table comprising a mapping relationship between a physical address and a virtual address of GPU display memory; determining a data cleaning queue corresponding to the GPU, the data cleaning queue being used for globally cleaning data in the GPU display memory; under the condition of locking the data cleaning queue, performing a driving upgrade operation on the GPU based on the driving upgrade request, obtaining a post-upgrade page table corresponding to the GPU, the post-upgrade page table comprising a mapping relationship between the physical address and the virtual address of the GPU display memory; and based on the pre-upgrade page table and the post-upgrade page table, regulating the data in the GPU display memory. In the embodiments, the driving upgrade operation of the GPU can be implemented without the need for operations such as display memory backup, shutdown and restart.

The application provides a GPU display memory and system memory cooperative management method and system of a cloud mobile platform, the method comprising: acquiring GPU display memory parameters of the GPU display memory and system memory parameters of the system memory of the cloud mobile platform in real time, and calculating a resource imbalance index and a unified stress value according to the GPU display memory parameters and the system memory parameters; constructing a unified resource view according to the GPU display memory parameters, the system memory parameters, the unified stress value and the resource imbalance index, and making corresponding cooperative scheduling decisions for the GPU display memory and / or the system memory based on the unified resource view; detecting a current session state of a user, adopting a corresponding resource allocation strategy according to the current session state, and adjusting resource allocation of the GPU display memory and the system memory through a resource smooth switching mechanism when the session state of the user is switched; and predicting an application to be started by the user based on historical behaviors of the user, and performing resource pre-allocation processing on the application to be started. The application can realize cooperative scheduling of the GPU display memory and the system memory.

The invention provides a video memory and memory fusion distribution method for a large neural network model, and belongs to the technical field of large neural network models, and the method comprises the steps: collecting system state data in real time, including a video memory, a memory utilization rate and related performance indexes; static and dynamic characteristic components are extracted by innovatively applying singular value decomposition, a multi-dimensional mapping relation model of molecular dynamics simulation is constructed, and a coupling state equation set of video memory allocation is established. And solving the equation set by adopting an ant colony optimization algorithm, generating a dynamic storage pointer, and establishing a multi-target storage scheduling equation set through joint characteristic decomposition to optimize resource utilization, access delay, fragment elimination, migration overhead and load balance. Algorithm parameters are updated by utilizing an entropy evaluation method, and finally collaborative scheduling of video memory and memory resources is realized in a unified storage management module, so that the calculation efficiency and the resource utilization rate of a neural network model are remarkably improved, and the problem that allocation of large model memories and video memories is not optimized enough in the prior art is solved.

The application relates to a method for realizing multi-layer video editing in nonlinear editing, comprising the following steps: receiving a pasting task; calculating a pasting range; distinguishing a color format; dynamically uploading a display card display memory; adopting different uploading strategies according to different parameter information, the strategies including two categories: a color format with a single-pixel image format and a color format with a complex-pixel image format, and each category has four cases for response; and pasting operation. The application processes the pasted video before pasting, and the video picture is a reduced window when displayed on the screen, so that the entire high-definition picture does not need to be uploaded when the display quality is guaranteed, only the original data needs to be quickly scaled according to the size of the corresponding picture displayed on the screen, the reduced image is uploaded to the GPU, and the GPU performs pasting, so that the operation layer number can be greatly improved, the CPU occupation can be reduced as much as possible, the uploading bandwidth of the GPU display memory can be reduced, and the real-time layer number is improved.

The application relates to an ultra-high-definition image restoration method, device and equipment based on a clustering center feature scanning. The method comprises the following steps: constructing a clustering center scanning unit and a space-channel feature modulator, the clustering center scanning unit constructs a plurality of center features through sparse sampling of an input feature map in a feature aggregation stage, calculates a cosine similarity matrix of pixels and the center features, filters similar pixels through an activation function and aggregates to generate a clustering core feature, and then establishes an association mapping of core and non-core features by using the similarity matrix through a score diffusion stage, transfers a global modeling weight, the space-channel feature modulator extracts global features and texture detail features in parallel attention branches, fuses the two modules based on an asymmetric encoder-decoder architecture, constructs an ultra-high-definition image restoration network, restores a low-quality ultra-high-definition image after training, and outputs a high-quality image. The method can effectively solve the existing technology's display memory bottleneck and detail blur problem.

The application discloses a large model long context window dynamic cataloging block addressing method and system, and belongs to the technical field of large model long context reasoning underlying scheduling. The system comprises a dynamic block classification module and an atomic addressing execution module. The dynamic block classification module performs dynamic cataloging block processing on the large model long context window according to data characteristics and establishes a mapping relationship. The atomic addressing execution module performs atomic level directional addressing based on the mapping relationship. In the addressing process, full-amount long context data is not loaded and full-amount context traversal retrieval is not performed. The corresponding method realizes long context scheduling optimization based on dynamic block and atomic addressing. The application can reduce the display memory occupation and invalid computing power loss, improve the long context reasoning efficiency and response speed, and adapt to various large model long context reasoning scenes.

The application relates to the technical field of dynamic modeling, and discloses a dynamic modeling method and system for a 3D home scene, which comprises the following steps: acquiring real-time interactive displacement vector data; when the capture frequency of the real-time interactive displacement vector data exceeds a fixed refresh rate threshold, fusing into a weighted mixed deformation vector through a cyclic temporary storage queue; calculating a local vertex attribute matrix correction value according to the weighted mixed deformation vector, and performing matrix internal superposition transformation on the local vertex attribute matrix correction value and a time sequence topological offset matrix to complete time sequence difference compensation correction; and transmitting the local vertex attribute matrix correction value into a sub-buffer area overwrite interface through a sparse vertex array slice stored in an interleaved structure to perform local in-situ overwrite writing, and updating a grid topological form, wherein the application limits the recalculation cost within a local slice range, reduces the throughput pressure of a display memory bus, eliminates time sequence lag, and avoids picture flickering.

The invention provides an early warning method and system for running performance abnormity of a graphics processor, and the method comprises the steps: calling a temperature monitoring interface and a video memory calculation interface based on any pre-obtained monitoring period; configuring the temperature monitoring interface and the video memory calculation interface to the graphic processor, and obtaining current temperature monitoring data and current video memory monitoring data; obtaining a temperature monitoring result based on the current temperature monitoring data and a preset temperature threshold; obtaining a video memory monitoring result based on the current video memory monitoring data and a preset video memory residual threshold value; and if the temperature monitoring result and / or the video memory monitoring result do / does not meet the preset operation requirement, generating an abnormity monitoring early warning signal so as to carry out early warning on the operation performance abnormity of the graphics processor. According to the invention, the monitoring serial port is periodically called to early warn the running performance abnormity of the graphics processor, and the running reliability of the graphics processor is improved.

The application discloses a short video generation method, and belongs to the technical field of video production. The method comprises the following steps: setting a webpage editor, performing user information registration verification, uploading video materials in the webpage editor when the verification is successful, performing target video production, producing webpage animation in the webpage according to a time axis through the rendering function of HTML5, rendering the obtained webpage animation through a browser, rendering each frame of picture in the webpage animation to the display memory of a display card, and generating a video in a corresponding format according to the rendered picture and corresponding audio. The method can produce a short video through drawing webpage animation in a general browser. The method does not need professional software, and can directly use the browser to render and generate a short video. Moreover, a template library is established, the user can conveniently produce a video, the template library is dynamically updated according to the use data of the user, and the template library gradually becomes more in line with the use habit of the corresponding user.

The present application relates to the technical field of scene rendering, in particular to a scene rendering method, device, electronic equipment and target vehicle. A target scene model corresponding to the target vehicle is built; based on a car machine screen corresponding to the target vehicle, a target texture image corresponding to the target scene model and a target flow rate image corresponding to the target texture image are constructed; the color and transparency of each pixel in the target scene model are rendered based on the target texture image and the target flow rate image, and a rendered background model is obtained. The memory and display memory overhead of the car machine is greatly reduced, providing reliable material support for subsequent real-time dynamic flow calculation, and the visual effect and the operation efficiency of the car machine are considered. At least 120 continuous sequence frame materials are not required. Different fluid effect requirements are adapted, and the lightweight calculation logic is compatible with the performance limitation of the car machine GPU, and the dynamic visual effect and the stability of the rendering frame rate are considered.