638 results about "PERQ" patented technology

The invention discloses a data center machine room AI energy-saving control method and system, a digital twin model of a machine room operation state is constructed through a holographic perception and heterogeneous data fusion technology, centimeter-level monitoring of an equipment state and environmental parameters is realized, and the system integrates a laser radar array, an acoustic sensor and a gas sensor network. The time-space alignment of multi-modal data is completed by combining edge computing nodes, holographic mapping including thermodynamic characteristics, vibration characteristics and gas leakage risks is formed, historical temperature control strategy characteristics are extracted by adopting a variational auto-encoder based on a dynamic strategy generation mechanism of generative artificial intelligence, and a load trend is predicted by combining a long-short-term memory network. Constructing a self-adaptive strategy pool; the multi-agent reinforcement learning framework enables temperature control, equipment scheduling and power grid response to form game optimization, the strategy robustness in a complex scene is improved, and the system innovatively fuses power grid real-time electricity price and carbon transaction data so as to establish a multi-target decision system.

The invention discloses a GPU (Graphics Processing Unit) and parallel IO (Input / Output) collaborative optimization method based on mode heterogeneous computing, and particularly relates to the field of heterogeneous computing optimizing.The method comprises the following steps: monitoring mode characteristics during execution of a target computing task in real time through an instruction analyzer, and synchronously collecting dynamic parameters of a heterogeneous computing environment to generate a multi-dimensional resource situation matrix; based on the mode and the resource situation matrix, collaborative optimization operation of the binding equipment dimension and the scheduling time dimension is executed; and constructing a three-level adaptive transmission mechanism and periodically implementing feedback optimization according to an execution state of the three-level adaptive transmission mechanism. According to the GPU and parallel IO collaborative optimization method based on mode heterogeneous computing, the data prefetching hit rate is increased by dynamically sensing the matching relation between a heterogeneous computing mode and an I / O access mode; end-to-end delay is reduced and task contention conflicts are reduced through a dynamic matching strategy of an equipment capability portrait and a task type; and the heterogeneous storage bandwidth peak value utilization rate and the I / O throughput are improved by differentially utilizing the hierarchical characteristics of the multi-stage storage.

Embodiments of the present invention provide computer-implemented methods, computer program product, and computer systems. One or more processors analyze user prompts using one or more natural language understanding techniques. One or more processors then enrich the user prompts by integrating contextual data from user interaction history and adapt the enriched user prompts to align with characteristics of Large Language Models (LLMs) and Application Programming Interfaces (API) requirements of the LLMs.

The invention provides a Linux access control system based on attributes, and relates to the technical field of data access control. The system comprises a system monitor module, a data interaction module and a decision unit. The system monitor module collects attributes from a kernel and a user space and writes the attributes into the data interaction module; the access decision unit compiles the access control strategy into an eBPF program and mounts the eBPF program to a corresponding hook; executing the kernel to the hook, and triggering an eBPF program; an eBPF program queries a Flow rule; matching the attribute with the Flow rule, and if the matching is successful, executing a corresponding action; if all the Flow rules fail to match, executing a default action; the system can be expanded during operation, and can be loaded or unloaded based on dynamic loading characteristics and strategies of the eBPF program and the eBPF program during operation of the system, so that the problem that a kernel needs to be compiled in a traditional LSM scheme is solved; the method does not intrude the kernel, is completely based on an eBPF program, does not modify a kernel source code, and can guarantee the stability and compatibility.

The invention relates to the technical field of numerical control, in particular to a control method and system of numerical control equipment and a medium. The method comprises the following steps: collecting workpiece surface temperature distribution data and obtaining a workpiece CAD model; importing the workpiece surface temperature distribution data into a workpiece CAD model for internal temperature conduction inversion to obtain a first workpiece internal temperature distribution diagram; identifying a non-key area of the workpiece; performing a pre-cutting test on the non-key area of the workpiece to collect the temperature in the cutting process; performing nonlinear thermal expansion modeling on the workpiece based on the cutting process temperature to obtain a workpiece thermal expansion characteristic model; and an internal temperature distribution diagram of the second workpiece is obtained, and the internal temperature distribution diagram of the second workpiece represents the initial thermal state of the workpiece before formal machining. The numerical control machining precision and the cooling system efficiency are improved, the machining cost and resource consumption are reduced, and the machining adaptability, flexibility and stability are enhanced.

The invention relates to the technical field of virtualization management, in particular to a virtual machine operation management system based on RISC-V. The system comprises an instruction set mapping module, a resource scheduling optimization module, a virtual machine monitoring integration module, an operation tuning update module and an operation configuration distribution module. According to the method, by analyzing the operation instruction of the virtual machine and combining the RISC-V underlying characteristics, accurate instruction mapping is achieved, the processing efficiency and accuracy are remarkably improved, the performance loss and conversion delay caused by too high abstraction level of a traditional virtual machine on the instruction level are overcome, the optimal allocation scheme is screened, the resource utilization rate and the system response speed are effectively improved, and the system performance is improved. The operation state and performance indexes of the virtual machine are integrated, anomaly detection and resource recovery are embedded, system stability and effective resource reutilization are ensured, basic configuration is continuously and incrementally updated, operation configuration refinement and automatic management and updating are achieved, the overall operation efficiency and management flexibility are improved, and the manual intervention cost is reduced.

Disclosed herein are system, method, and computer program product embodiments for detecting anomalies during software testing. The methods include generating a plurality of test reports for the software program by executing one or more test cases on a plurality of versions of the software program, generating a control chart based on the plurality of test reports, generating an alert when at least one testing characteristic includes an anomaly over the plurality of versions of the software program as determined based on the control chart. The control chart includes a plot associated with at least one testing characteristic of the software program, and a historical context associated with execution of the one or more test cases on the plurality of versions of the software program.

According to the big data management-based data labeling method and system provided by the invention, efficient, accurate and intelligent data labeling is realized by integrating multi-virtual machine collaborative labeling, multi-model fusion labeling, adaptive data preprocessing and hierarchical cleaning and a multi-dimensional task scheduling and dynamic load balancing mechanism. The method comprises the steps that self-adaptive preprocessing and layered cleaning are conducted on original big data, noise is removed, missing values are filled up, and format conversion is completed; dividing the preprocessed data into a plurality of subtasks according to data characteristics; distributing the sub-tasks to different virtual machine instances for parallel processing by utilizing a multi-virtual machine technology; labeling the same data fragment on each virtual machine by adopting a multi-model labeling mechanism; adopting a weighted fusion or voting mechanism to generate a comprehensive annotation result for the output results of the multiple models in each virtual machine; and summarizing the labeling results of the virtual machines to form a global data labeling result.

The invention discloses a power consumption and performance balanced scheduling method and system for a heterogeneous multi-core processor, and belongs to the technical field of computers, and the method comprises the steps: obtaining historical load data and current system state parameters, generating a load sequence and carrying out load prediction analysis, generating a predicted load value for feature fusion and quantification, and generating a task feature vector; constructing a core capability portrait, calculating a matching degree between the task characteristic vector and the core capability portrait, and generating a scheduling strategy; and dynamically combining the physical cores into a logic calculation unit according to a scheduling strategy, configuring a power consumption state, and executing task allocation and migration. According to the method, the technical means of load prediction analysis, quantitative matching of tasks and cores and dynamic combination and configuration of physical cores are adopted, and pre-judgment and prospective distribution of system resources can be achieved, so that performance requirements are met, meanwhile, the system energy efficiency is effectively optimized, and deep balance of power consumption and performance of a processor is achieved.

The invention provides a GPU (Graphics Processing Unit) resource virtualization computing power scheduling method. The method comprises the following steps of: obtaining a task and determining a computing demand characteristic and a task attribute of the task; determining a resource demand according to the calculation demand characteristic and the task attribute; determining task priorities according to the task attributes; and determining a scheduling result of the GPU resource according to the task priority and the resource demand. The GPU resource of the task is allocated through the specific task attribute, the high efficiency of GPU operation is ensured, the computing power resource is allocated in a balanced manner, the utilization rate of the GPU is improved, the balance of the task load is ensured, and the task is completed more efficiently.

The invention discloses a hierarchical dynamic scheduling method based on a strategy optimization DDQN algorithm, which is used for solving a dynamic scheduling problem of a reentrant hybrid flow shop with a batch processor, and comprises the following steps: firstly, determining an objective function and a constraint condition of the scheduling problem; secondly, by introducing a self-attention mechanism, providing a layered structure based on the self-attention mechanism DDQN, and constructing two agents, namely a batching agent and a scheduling agent, to respectively solve batching sub-problems and scheduling sub-problems in the problem; besides, in order to cope with the multi-stage batch processing and reentry scheduling characteristics in the problem, a Markov decision process considering the characteristics of the two agents is designed, and the Markov decision process comprises states, actions and rewards. Furthermore, an action selection strategy and a soft start target network updating strategy based on a mask combined with an epsilon-greedy strategy are provided, so that the efficiency and generalization ability are improved. The method has a remarkable effect on solving the dynamic scheduling problem of the reentrant hybrid flow shop with the batch processor.

The invention discloses a deployment method and device of a large model agent, equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: determining agent configuration information of a to-be-deployed large model agent after an agent deployment request is received, and determining a target large model and model metadata; determining an available resource condition of a preset computing resource pool, and performing query matching according to the available resource condition and the model metadata to determine a plurality of hardware-compatible candidate computing resource nodes; performing load prediction operation on the to-be-deployed large model agent after the large model agent is online to obtain a predicted load, and generating a target deployment decision scheme based on the predicted load, a preset scheduling strategy, the available resource condition and the candidate computing resource node; and adjusting the runtime parameters of the target large model according to the resource characteristics of the target computing resource node, and loading the adjusted target large model on the target computing resource node so as to deploy and start the agent instance of the to-be-deployed large model agent.

The invention is suitable for the field of data processing, and discloses a remote control method of an experiment sandbox, terminal equipment and a storage medium. The remote control method of the experiment sandbox comprises the following steps: if an experiment request initiated by a user side is received, configuring the experiment sandbox according to identity information carried by the experiment request, and querying experiment sandbox connection information corresponding to the identity information; selecting an active target Guacd instance from the Guacd cluster, and establishing an RDP session channel with the experiment sandbox according to the target Guacd instance and the connection information of the experiment sandbox; and responding to a trigger instruction of the user side according to the RDP session channel. The RDP session channel is constructed through the protocol conversion capability of the Guacd cluster, so that the hardware acceleration characteristic of the remote desktop of the Windows system can be fully played, and high-frame-rate graphic instruction transmission is realized.

The invention discloses a comprehensive performance evaluation device and method for domestic credit and creativity platform hardware, and the method comprises the implementation steps: constructing a hybrid load task, generating a hybrid load task description file adaptive to the characteristics of domestic hardware, analyzing and executing a dynamic test task, and collecting hardware performance data in real time. And carrying out quantitative scoring by adopting a reference comparison method, generating a radar map portrait, and carrying out multi-dimensional performance evaluation on a domestic processor, a memory, storage and network equipment. According to the method, based on customized instruction extension characteristics of a domestic credit and creativity platform, evaluation deviation caused by mismatching of a traditional evaluation architecture is eliminated through domestic hardware load adaptation; a dynamic hybrid load technology is introduced, so that response robustness and resource cooperation efficiency meeting dynamic load requirements in a high-complexity scene are realized; a hardware performance quantification algorithm and a visualization technology are combined, and an intuitive and practical performance analysis tool is provided.

The invention provides a multi-core log management architecture and method based on a power gap operating system and a computer program product, which are suitable for the technical field of computers, and comprise a master core, a slave core and a shared memory area, the slave core further comprises a log generation module, a buffer module and a log uploading module; the main core is responsible for operating a power gap operating system; the slave core is responsible for running a naked running program or a real-time operating system; the log uploading module writes target log data in the buffer module into a shared memory area when the data cached in the buffer module reaches a preset condition; under the condition that the master core monitors that the slave core uploads the target log data to the shared memory area in the shared memory area, the target log data in the shared memory area is read, and integration, classification and storage operation is conducted on the target log data in sequence. Therefore, the efficiency problem of log collection, storage and management in the multi-core heterogeneous architecture can be solved, the characteristics of the master core and the slave core are fully utilized, and the log processing capacity of the system is improved.

The invention discloses an automatic integrated system from an asynchronous pipeline to an asynchronous circuit, which adopts a modular architecture, takes a high-level structure description file in a JSON / XML format as input, and gradually maps to generate a gate-level netlist and a standard delay format file so as to be in butt joint with a commercial back-end design process. According to the method, asynchronous design based on an asynchronous structure can be automatically mapped into an asynchronous circuit, the automatic mapping process can seamlessly process multi-level design representation, the mapping result is stable and cooperatively operated, asynchronous circuit time sequence detection and delay matching are automatically completed, the design efficiency is greatly improved, and the design cost is reduced. An automatic delay matching mechanism enables the circuit to have a good data ready detection and handshake mechanism, and the characteristics of low power consumption, high throughput and no global clock drift sensitivity are realized; in addition, automation of asynchronous design key links such as structure abstraction, time delay modeling and testability insertion is achieved while design readability, hierarchical consistency and time sequence controllability are guaranteed.

The invention relates to the technical field of printing and typesetting, and provides a method and system for creating a printing template through a user-defined report. Template elements and typesetting instructions input by a user are received through a graphical interface; constructing an API (Application Program Interface) port in which the template element is dynamically associated with the heterogeneous data source; configuring a programmable logic judgment mechanism at an API port, and determining medium characteristics corresponding to the template elements; wherein the programmable logic judgment mechanism is used for determining a display / hiding state and a style parameter of a template element based on a preset compilable rule; according to the medium characteristics and the typesetting instruction, a paging strategy is determined, the element spacing and the typesetting proportion are dynamically adjusted, and a target printing template is generated. Through an API port and a programmable logic judgment mechanism, business rules are embedded into template generation logic, intelligent decision of element display / hiding is realized, element spacing is calculated in real time based on medium physical attributes such as paper size and material expansion and contraction rate, and the problem of content truncation during cross-medium printing is solved.

The invention relates to the field of industrial Internet of Things, in particular to an edge computing communication method and system for the industrial Internet of Things, and the method comprises the following steps: 1, a user issues a task to a service platform through a user platform, and after the service platform receives a task request, the service platform sends the task request to the user platform based on a device type and a task type associated with the task; classifying and marking the tasks, and determining real-time levels of the tasks and importance weights of associated production links; 2, the service platform transmits the classified tasks to a corresponding service sub-platform, the service sub-platform obtains historical operation data and edge node basic information of task associated equipment, generates a first calculation task carrying a task attribute tag according to a classification result, and sends the first calculation task to a management platform; and step 3, the management platform carries out unified management on the plurality of first computing tasks. By adopting the technical scheme of the invention, industrial scene characteristics can be fit, and task priority, resource dynamics and network adaptability are considered.

Apparatuses, systems, and techniques to perform an application programming interface (API) to identify processor settings to be used when performing one or more software workloads. As an example, one or more processors comprising one or more circuits perform an API to indicate one or more computing resources to be used by one or more instructions based, at least in part, one or more characteristics of that software workload.

The invention relates to a method, a device, equipment and a medium for dynamically configuring a window control and layout, and the method comprises the following steps: firstly, obtaining and analyzing an XML configuration file to generate a data model tree of a structured window interface in a memory; then, objects are dynamically created based on a Qt reflection mechanism, attributes and signal slots are set, Qt reflection characteristics are fully utilized, object creation and attribute processing are flexible and efficient, hard coding interface elements in the compiling stage are not needed, needed controls and layouts can be dynamically generated according to a data model tree, and the dynamic nature and expandability of interface configuration are greatly enhanced; establishing a set membership tree between the controls and the layouts in the recursive traversal process to obtain a complete interface tree; and finally, performing layout calculation and rendering to generate a display interface, so that automation of interface layout is realized, interface element layout can be automatically adjusted according to a data model tree structure, and efficient dynamic configuration of window controls and layout is realized.

The invention provides a method, a system and equipment for improving the computing performance stability of a hardware platform and a medium, and belongs to the technical field of computer system performance optimization. The method comprises the following steps: acquiring architecture characteristic data of a bottom hardware platform through a hardware detection tool, and generating and loading a first-stage system kernel parameter configuration based on the architecture characteristic data; reading the architecture characteristic data, carrying out behavior analysis and type identification on the running process based on the architecture characteristic data, and generating a second-level process scheduling strategy according to the behavior analysis and type identification; reading cache structure information in the architecture characteristic data, and driving a file system to intelligently prefetch and reconstruct a storage layout of memory data based on the cache structure information; and continuously collecting performance index flow data when the system runs, performing real-time analysis on the performance index flow data by using a performance degradation model, generating a feedback control instruction according to an analysis result, and dynamically correcting the kernel parameter configuration of the first-stage system and the scheduling strategy of the second-stage process.

The invention discloses a heterogeneous resource energy-saving optimization scheduling method and system based on computing power perception, and relates to the technical field of modern computing infrastructure, the system comprises a computing power-energy consumption evaluation module, the computing power-energy consumption evaluation module is used for carrying out computing power and energy consumption evaluation on heterogeneous resources, generating and dynamically updating a computing power-energy consumption mapping table, the heterogeneous resources comprise ARM architecture resources, X86 architecture resources and GPU resources. According to the method, the computing power-energy consumption mapping table is generated and updated in real time, so that the scheduling decision is always based on the latest energy efficiency state of the resources, the accuracy of the basic data is ensured, intelligent task classification and dynamic constraint construction are combined, the system can flexibly balance the task performance and the energy consumption target, and particularly, the strategy can be adaptively adjusted for a high-emergency task; the timeliness of key services is guaranteed, the differentiated scheduling strategy serves as an efficient pre-screening mechanism, task requirements and resource architecture characteristics are accurately matched, and the pertinence and efficiency of resource allocation are remarkably improved.

The invention relates to the technical field of task execution, and provides a workflow parallel computing execution method and system, terminal equipment and a storage medium. The workflow parallel computing execution method comprises the steps that a to-be-executed task is obtained, and after the to-be-executed task is subjected to logic analysis, the to-be-executed task is obtained; dividing a to-be-executed task into a plurality of sub-tasks according to the task type, constructing a task dependency graph, and making an execution model according to the characteristics of the sub-tasks; according to the resource states and the task priorities of the sub-tasks, resource allocation is carried out on the sub-tasks, and an execution sequence is set for the sub-tasks based on the dependency relationship in the task dependency graph; according to the execution mode and the execution sequence, the subtasks enter a parallel execution state, and an execution result of each subtask is obtained; and according to the original logic and data dependence of the to-be-executed task, summarizing, sorting and combining the execution results to obtain a summarized result, and verifying the summarized result to obtain a final execution result.

The embodiment of the invention discloses a rendering task rendering method and device, equipment and a medium. The rendering task rendering method comprises the steps that a specified rendering task is transferred to a Worker thread from a UI thread; dynamically configuring parameter information of a specified rendering task based on hardware characteristics of an environment where the Worker thread is located; setting a rendering mechanism of the specified rendering task based on the parameter information; and rendering the specified rendering task based on the rendering mechanism to obtain a rendering result of the specified rendering task. According to the method, the rendering task is stripped from the UI thread to the Worker thread, the blocking risk of the main thread is fundamentally eliminated, meanwhile, the rendering parameters are dynamically generated based on the real-time hardware characteristics of the Worker environment, the three major mechanisms of multi-stage buffering, tile rendering and layered rendering are coordinated and linked under unified configuration, a rendering strategy precisely matched with the hardware capability is formed, and the rendering efficiency is improved. Therefore, the cross-platform rendering robustness and the resource utilization efficiency of the high-end and low-end equipment are remarkably improved while smooth interaction experience is guaranteed.

The invention relates to a performance evaluation method for an ACE (Adaptive Cycle Engine) and electronic equipment. The method comprises the following steps: acquiring a to-be-evaluated ACE complete machine zero-dimensional simulation model, an adaptive fan high-fidelity simulation model, and working conditions and control rules of the to-be-evaluated ACE complete machine zero-dimensional simulation model; coupling the obtained models to obtain an ACE multi-dimensional coupling simulation model, and operating under the obtained working condition and control rule to obtain the ACE performance to be evaluated and the performance of each component in the ACE performance; according to the ACE multi-dimensional coupling simulation model, characteristic curves in an ACE complete machine zero-dimensional simulation model are adopted to represent characteristics of different ducts of a self-adaptive fan in the ACE complete machine zero-dimensional simulation model, and based on the difference of simulation results between the ACE complete machine zero-dimensional simulation model and the self-adaptive fan high-fidelity simulation model, the self-adaptive fan high-fidelity simulation model is obtained. The method is obtained after coupling is realized by continuously iteratively adjusting the scaling factor of the characteristic curve, so that the simulation precision of the self-adaptive fan is improved, and the overall performance evaluation accuracy is improved.

The invention discloses a controller programming method and device based on an equipment model, equipment, a medium and a product, the equipment model is used as a unified semantic anchor point, heterogeneous characteristics of physical equipment are converted into computable structured description, hardware adaptation and business logic are decoupled through a driving framework, a large model focuses on generation of a high-value control strategy, and the control strategy is optimized. Semantic drift and logic illusion of a program generation large model are remarkably inhibited by relying on double constraints of equipment document data and a knowledge graph, finally, an executable drive program meeting strict requirements of an industrial site is output through compiling verification of a closed loop, and due to the fact that manual development is not needed, development efficiency is improved, development cost is reduced, and development efficiency is improved. The equipment model provides a cross-protocol and cross-manufacturer standardized interface contract, so that the problem of poor reusability in traditional development is solved, and the reusability is improved.

The invention provides a model-based consumption type process planning method in a three-dimensional environment. The method comprises the steps of preprocessing design data and reconstructing an EBOM structure; a PBOM structure is constructed in a consumption type distribution mode; constructing an MBOM top layer structure by adopting a consumption type distribution mode; completing the definition of manufacturing items in a consumption type distribution mode; and issuing the MBOM structure. According to the process planning method adopted by the invention, planning is carried out in a three-dimensional space by completely depending on a model entity structure, and the planning of the process flow is efficiently completed by utilizing the accuracy and high-precision characteristics of the three-dimensional model. According to the method, consumption distribution of a product structure, construction of a BOM structure and manufacturing definition can be realized in a three-dimensional environment, so that a process planning task can be accurately and rapidly completed in a visual perspective.

The invention relates to a quantum measurement and control task compiling method and device, computer equipment and a storage medium. The method comprises the following steps: converting a quantum measurement and control task into an intermediate representation instruction matched with a quantum low-temperature measurement and control chip through a pre-constructed hardware behavior model of the quantum low-temperature measurement and control chip; the hardware behavior model is constructed according to hardware characteristics of the quantum low-temperature measurement and control chip; performing parallel scheduling on the intermediate representation instruction to obtain a scheduling result; the intermediate representation instruction is converted into hardware executable codes according to the scheduling result, compiling of the quantum measurement and control task is completed, and the hardware executable codes are used for indicating the quantum low-temperature measurement and control chip to conduct quantum calculation. By adopting the method, the high efficiency and reliability of the measurement and control chip in the low-temperature environment can be improved.

The invention provides a memristor based on a quasi 2D / 3D heterojunction perovskite and a preparation method and application of the memristor. The invention belongs to the technical field of memristors. In the memristor, a three-dimensional (3D) (FAPbI3) 0.95 (MAPbBr3) 0.05 perovskite thin film and a CF3-PEAI quasi-two-dimensional perovskite thin film are prepared by adopting a spin coating method and are used as functional layers of the memristor. The device has a stable I-V cycle characteristic, not only can realize a stable conductivity adjustable characteristic under positive and negative voltages, but also can accurately simulate a recognition task of a handwritten data set by utilizing the device and linear updating for enhancing and inhibiting a conductivity weight, and the accuracy rate can reach 94%. The invention aims to provide the perovskite memristor with a novel structure so as to meet the requirements of efficient neural synaptic bionic and brain-like computing system construction.

The invention provides a cloud edge collaboration algorithm arrangement and deployment method, system and device and a storage medium, and relates to the technical field of cloud edge collaboration.The method comprises the steps that algorithm task requirements input by a user are analyzed, and after corresponding task information is obtained, an intermediate representation file is generated; collecting computing power state information of the plurality of edge devices to determine a target edge device used for executing an algorithm link, and generating an operation parameter configuration file according to a hardware architecture of the target edge device and algorithm characteristics of the intermediate representation file; and issuing the intermediate representation file and the operation parameter configuration file to the target edge device, and performing automatic compiling and deployment according to the chip type of the target edge device. By issuing the intermediate representation file and the operation parameter configuration file to the target edge device and automatically executing compiling and deployment, the effects of cross-platform automatic adaptation, rapid deployment and efficient operation are achieved, and the problem that in the prior art, task organization and deployment flexibility is insufficient is solved.