182results about "Program saving/restoring" patented technology

This disclosure describes a large language model (LLM)-based agent operating system comprising an application layer, a kernel layer, and a hardware layer. The kernel layer comprises an AIOS kernel comprising: LLM core(s), an agent scheduler, a context manager, a memory manager, a storage manager, and a system call interface configured to manage interactions among the agent scheduler, the context manager, the memory manager, and the storage manager.

The invention is suitable for the technical field of terminals, and particularly relates to a memory management method, electronic equipment and a computer readable storage medium. According to the method, when it is detected that the first application is switched to the background state, the electronic device can determine that the first application does not need to display an image and does not need to carry out graphic rendering, that is, it can be determined that the first application does not need to use a GPU physical memory currently. At the moment, the electronic equipment can store the first content stored in the first GPU physical memory corresponding to the first application to a disk, and can release the first GPU physical memory, so that the occupation of the GPU physical memory is reduced, the remaining available physical memory of the electronic equipment can be increased, the response speed of the electronic equipment to user operation is increased, the fluency of the system is improved, and the user experience is improved. And user experience is improved.

The embodiment of the invention discloses a thread priority adjustment method and related equipment which are applied to electronic equipment, and the electronic equipment runs a first application. A first process of the first application comprises a plurality of first threads; identifying an associated thread of the first thread from the threads of the second process; the second process is a process which is operated by the electronic equipment, except the first process and the resident process and provides service for the first application; when it is detected that the running state of the first application is changed, the priority of the first thread is adjusted, the priority of the associated thread is adjusted, and the priority adjustment trend of the associated thread is consistent with the priority adjustment trend of the first thread. By adopting the embodiment of the invention, the response speed and performance of the system can be improved, and the user experience is improved.

The invention discloses an agent context management system and device based on importance sampling, and belongs to the technical field of artificial intelligence and agents, the agent context management system and device based on importance sampling comprise a global context manager used for maintaining and managing eight types of context information; the task stack manager is used for receiving a new request and performing task splitting; and the recursive execution engine is used for executing the task in a recursive mode and controlling the recursive depth. Eight types of context information are maintained through a global context manager, splitting and storage of complex tasks are achieved through a task stack manager, a recursive execution engine provides an efficient task execution mechanism and controls the recursive depth, an importance sampler selects related contexts based on a joint probability model, and the task execution efficiency is improved. And the context compressor combines the sampling fragments into a final context, and the task scheduler coordinates the working process of each component, so that a complete agent collaborative context management system is constructed.

The invention provides a frozen screen processing method and electronic equipment. The first component can be displayed on a screen of the electronic device. The first component has the ability to respond to a first operation. When a first operation on the first component is detected, the electronic device may detect whether the first component responds to the first operation. If the first component does not respond to the first operation, the electronic device can redraw the first component on the screen. According to the method, whether the frozen screen occurs in the electronic equipment or not can be detected according to whether the component displayed on the screen responds to the user operation or not, and when the frozen screen occurs in the electronic equipment, the component required to be used by the user is quickly recovered and responded by locally redrawing the component, so that the frozen screen problem is quickly solved, and the waiting time of the user is shortened.

Certain aspects of the present disclosure provide techniques for hardware-based saving and restoring of architecture state information for processing elements (PEs). According to certain aspects, one or more circuit elements trigger saving of architecture state information of at least one PE to at least one memory prior to the at least one PE transitioning from a first state to a second state and triggering restoration of the architecture state information from the at least one memory to the at least one PE prior to the at least one PE transitioning from the second state to the first state.

Techniques are provided for backing up virtual machines from a computing environment to a storage environment. A virtual machine agent is utilized to generate a snapshot of the virtual machine. Metadata comprising a snapshot identifier of the snapshot and virtual disk information of virtual disks captured by snapshot is generated at the computing environment. The metadata is retrieved and used to create a metafile that is transferred to the storage environment within which snapshots of the virtual machine are to be stored. The snapshot is retrieved from the computing environment and is packaged into a snapshot package having a protocol format used by the storage environment. The snapshot package is transferred to the storage environment.

Techniques are disclosed for capturing information surrounding a user's interactions with an application for enriching application context to be used by a digital assistant for supporting the user's interactions. In one aspect, a method includes detecting an event from a client device, where the event is associated with a user's interaction with an application on the client device. In response to detecting the event, application context is obtained for the application. The obtaining includes accessing the application context from a data store based on an identifier. A first generative artificial intelligence model can then be used to generate a list having an executable action based on the event and the application context. An execution plan is then created and executed, which includes executing the executable action using an asset to obtain an output. The output or a communication derived from the output is sent to the client device.

Certain aspects of the present disclosure provide techniques for hardware-based saving and restoring of architecture state information for processing elements (PEs). According to certain aspects, techniques involve triggering, via one or more circuit elements, saving of architecture state information of at least one processing element (PE) to at least one memory prior to the at least one PE transitioning from a first state to a second state; and triggering, via the one or more circuit elements, restoration of the architecture state information from the at least one memory to the at least one PE prior to the at least one PE transitioning from the second state to the first state.

The invention provides a learning machine voice instruction interaction method and system, is applied to the technical field of learning machines, and realizes fine management of help seeking of a user by starting an independent'temporary session state record 'for each knowledge point. By generating'multi-level guide prompts' and'multi-level question exploration ', the system can gradually guide the user to think instead of directly giving answers, so that not only is the independent thinking ability of the user cultivated, but also the system can more accurately judge the real mastering degree of the user on the knowledge point. When the user answers correctly, the system confirms the mastering of the user; and when the answer is incorrect, the system adjusts an auxiliary strategy, such as recommending a teaching video, so that more targeted help is provided. Therefore, according to the method provided by the invention, false triggering of dependence intervention caused by multi-user sharing can be avoided, the accuracy and individuation of an auxiliary strategy of the learning machine are ensured, and the user experience and learning efficiency are remarkably improved.

The present disclosure relates to a method for configuring a relay register module, including: receiving a start allocation request for at least one task sent by a task scheduler; determining, based on the start allocation request, a number of relay registers to be allocated to each task of the at least one task; allocating the corresponding number of relay registers to each task; and sending a wake-up signal to the task scheduler in a case where the allocation is completed, the wake-up signal is used by the task scheduler to start a task to which relay registers are allocated; wherein the relay register module is configured to store an intermediate result obtained from an operation based on an instruction of the task. The present disclosure further relates to an apparatus for configuring a relay register module.

Certain aspects of the present disclosure provide techniques for hardware¬ based saving and restoring of architecture state information for processing elements (PEs). According to certain aspects, one or more circuit elements trigger saving of architecture state information of at least one PE to at least one memory prior to the at least one PE transitioning from a first state to a second state and triggering restoration of the architecture state information from the at least one memory to the at least one PE prior to the at least one PE transitioning from the second state to the first state.

Techniques are provided for orchestrating operations between a storage environment and a computing environment hosting virtual machines. A virtual machine proxy, associated with a computing environment hosting a virtual machine, is accessed by an orchestrator to identify the virtual machine and properties of the virtual machine. A storage proxy, associated with a storage environment comprising a volume within which snapshots of the virtual machine are to be stored, is accessed by the orchestrator to initialize a backup procedure. The orchestrator utilizes the virtual machine proxy to create a snapshot of the virtual machine. The orchestrator utilizes the storage proxy to back up the snapshot to the volume using the backup procedure.

Approaches presented herein provide for the management of resources to be used to process a request, such as may involve orchestration of nodes for an inference request. Upon receiving an inference request, an orchestrator can determine a sequence of context nodes and inference nodes to be used to process the inference request, based in part upon a determined class of inferencing to be performed. The orchestrator can append metadata to the inference request that identifies the sequence, and can transmit the appended request to one or more first nodes in the sequence. If the nodes have a network programmable device, or similar capability, the request can be forwarded to the nodes in sequence without having to go back to the orchestrator between nodes.

A method of managing resources in a graphics processing pipeline includes, in response to selecting a task for execution within a texture / shading unit, allocating to the task both a static allocation of temporary registers for the entire task and a dynamic allocation of temporary registers. The dynamic allocation comprises temporary registers used by a first phase of the task only and the static allocation of temporary registers comprises any temporary registers that are used by the program and are live at a boundary between two phases. When the task subsequently reaches a boundary between two phases, the dynamic allocation of temporary registers are freed and a new dynamic allocation of temporary registers for a next phase of the task is allocated to the task.

An apparatus includes an instruction decoder and a processing circuitry system. In response to a data structure processing instruction specifying at least one input data structure identifier and an output data structure identifier, the instruction decoder controls the processing circuitry system to perform processing operations on at least one input data structure to produce an output data structure. Each input / output data structure includes a data arrangement corresponding to multiple memory addresses. The apparatus includes two or more sets of one or more data structure metadata buffers, each set associated with a corresponding data structure identifier and designated to store metadata indicating the memory address of the data structure identified by the corresponding data structure identifier.

Certain aspects of the present disclosure provide techniques for hardware-based saving and restoring of architecture state information for processing elements (PEs). According to certain aspects, one or more circuit elements trigger saving of architecture state information of at least one processing element (PE) to multiple memories prior to the at least one PE transitioning from a first state to a second state, wherein the architecture state information comprises information associated with different hierarchical levels and trigger restoration of the architecture state information from the multiple memories to the at least one PE prior to the at least one PE transitioning from the second state to the first state.

In an example, an apparatus comprises a plurality of execution units, and a first memory communicatively couple to the plurality of execution units, wherein the first shared memory is shared by the plurality of execution units and a copy engine to copy context state data from at least a first of the plurality of execution units to the first shared memory. Other embodiments are also disclosed and claimed.

An electronic device capable of performing multi-camera intelligent switching and a multi-camera intelligent switching method thereof are provided. The electronic device includes a plurality of camera device media foundation transform (camara DMFT) units, an integrated DMFT unit and a mix camera agent. Each of the camera DMFT units is connected to one of a plurality of cameras. The integrated DMFT unit is serially connected to one of the camera DMFT units. The mix camera agent is connected to the cameras. The mix camera agent is used for obtaining a switching notification signal. The integrated DMFT unit switches a serial path between the integrated DMFT unit and one of the camera DMFT units according to the switching notification signal.

An application processing method is performed by an electronic device. The electronic device includes a first processor and a second processor, the first processor running a first operating system, the second processor running a second operating system. The method includes: entering an application management interface in the first operating system, the application management interface displaying an application processing entry of a first application installed in the second operating system; and in response to a triggering operation performed on the application processing entry of the first application, entering a management item interface of the first application. An application management item of the first application is displayed in the management item interface of the first application.

The invention belongs to the technical field of memory scheduling. The invention discloses a memory scheduling and application acceleration method for an end-side heavy load scene. According to the embodiment of the invention, in a cold start process oriented to GB-level large-scale applications, in a multi-task scene of a mobile terminal, a vehicle-mounted terminal and the like, by uniformly scheduling a selective file preloading module, a self-adaptive memory recovery module and a context-aware process termination module, on the premise that application program codes are not modified, the application program codes can be quickly and efficiently started, and the application program codes can be quickly and efficiently started. The method comprises the following steps: modeling a file access mode and page type characteristics related to cold start, dynamically adjusting a preload object, a recovery strategy and a process termination sequence based on a preload memory budget and real-time memory pressure, preferentially retaining a key preload page, and selecting a background application with a relatively high net releasable memory and a relatively low short-term restart probability to terminate; and collaborative optimization of the cold start time delay and the background survivability under the constraint of the limited memory and the I / O bandwidth is realized.

A method including processing a stream of data in a sequence of tasks. The processing including receiving a first block of data of the stream of data, determining features associated with the first block of data, selecting, based on the features, one of a first a task to process the first block of data or a second task to process the first block of data and if the second task is selected, shift an output of the second task in time to align the output of the second task with a predicted output of the first task processing a second block of data of the stream of data.

This application provides a state management method and apparatus, and an intelligent driving device. The method includes: receiving a state switching request sent by a first service node, where the state switching request includes a target state of the first service node; determining information about an extended task based on the state switching request, where the extended task is associated with at least one other service node, and there is a dependency relationship between the at least one other service node and the target state; and controlling an action of the first service node based on the information about the extended task, where the action includes switching to the target state or maintaining a current state. The method in this application may be applied to the intelligent driving device, for example, an intelligent vehicle or an electric vehicle. When state information of all services cannot be directly obtained, state management for a service in a system may still be implemented. This helps implement decoupling between a state management framework platform and a service layer, and helps independent evolution and mutual compatibility of an intelligent driving computing platform and an intelligent driving service.

An apparatus comprises exception return state register storage, and processing circuitry. In response to a guarded control stack (GCS) exception return state push instruction, the processing circuitry obtains exception return state information from the exception return state register storage and push the state information to a GCS data structure. In response to a GCS exception return state pop instruction, the processing circuitry obtains GCS-protected exception return state information from the GCS data structure. In at least one operating state, the processing circuitry detects, in response to an attempt to modify the exception return state information stored in the exception return state register storage, whether an exception return state lock parameter is in a locked state or an unlocked state, and signals a fault when it is in the locked state.

The invention relates to the technical field of artificial intelligence application, and provides a multi-agent cooperation-based invoice intelligent auditing system, which comprises an invoice access analysis module, a multi-agent auditing module, a rule management module, a result aggregation early warning module and a visual filing module, and the multi-agent auditing module is used for performing auditing, duplicate checking, compliance and accounting operations on the structured invoice data through a plurality of parallel agents to generate auditing sub-results of each agent. The system simultaneously performs auditing, duplicate checking, compliance and accounting operations on the invoice data by setting the plurality of parallel agents; and a plurality of key auditing links which must be executed in series originally are parallelized, so that the enterprise financial processing efficiency is improved.

A method for optimizing cache reuse in a computational system involves assigning unique identifiers to various Tweaks that affect computational outcomes and injecting Nodes with fields that form a bitmask representing these Tweak dependencies. During execution, the system tracks and updates each Node's dependency information, adjusts the cache key based on the actual Tweak dependencies identified, and stores a proxy in the cache for each executed Node within a Scenario. This proxy enables efficient cache reuse by matching with other Scenarios that share overlapping Tweak dependencies.

The present disclosure relates to apparatuses and methods of capturing register state. Some aspects of the present disclosure relate to an apparatus comprising a register circuit implementing a plurality of registers, and a processing circuit to perform data processing operations on data stored in the registers. The apparatus comprises a store buffer circuit to temporarily store given data prior to providing the given data to a memory in response to a store instruction on the given data. In response to receiving a request at the processing circuit to perform a state save trigger operation, the register circuit is configured to capture a state of a subset of registers of the plurality of registers in shadow registers of the register circuit, and to provide the captured state from the shadow registers to the memory.

The invention discloses a fluid pulsation accelerator architecture for reinforcement learning of a large language model, and belongs to the technical field of artificial intelligence hardware acceleration. The system aims at solving the problems that when a current universal processor executes an RLHF working load, an instruction driving normal form is not matched with data flow calculation, fixed parallel granularity cannot adapt to a dynamic load, and the efficiency is low due to the fact that a framework does not sense data statistical characteristics. The core of the system is a liquid systolic array calculation fabric capable of being dynamically reconstructed, execution is triggered through data flow, and kernel boundaries and instruction overhead are eliminated. According to the system, a global lookup table subsystem is fused, and nonlinear calculation is optimized through merging query and parallel lookup by using data distribution prior; and a dynamic scheduling unit is configured, and elastic parallelism is realized by adopting a resource allocation algorithm supporting work stealing. According to the method, the throughput and the energy efficiency of RLHF training and a large language model reasoning stage can be remarkably improved, and a new design normal form is provided for a next-generation AI special computing architecture.

A method, computer program product, and computing system for dividing a speech signal into a plurality of chunks. A first context window is defined with a first period of past context for processing the plurality of chunks with a neural network of a speech processing system. The neural network is trained using the first context window. A second context window is defined with a first period of past context for processing the plurality of chunks with the neural network. The neural network is trained using the second context window.