91 results about "Computer performance" patented technology

The invention provides a computer hardware performance evaluation method and system based on an analogue simulation model, and relates to the technical field of computer performance evaluation. According to the method, hardware component models such as a processor, a memory and I / O are constructed by analyzing a system structure description file, semantic analysis is performed on an instruction stream or a parallel computing graph of a to-be-evaluated application, and a task load model is formed. The model is input into an event-driven scheduling module, simulation is executed on the hardware component model, task-resource mapping is generated, and task time delay, communication traffic and power consumption are recorded. And calculating average response time delay, data bandwidth and unit energy consumption according to the simulation data, and outputting an evaluation report compared with the performance baseline. According to the method, real load-oriented multi-dimensional performance prediction can be realized, and the method can be used for architecture optimization and scheme selection.

In some aspects, a cloud-based computer system includes: a quantum computing system comprising a quantum processing unit; a container management and execution system configured to receive a container and execute a program within the container; and a communication channel between the container management and execution system and the quantum computing system for providing program instructions to the quantum computing system. The container management and execution system and the quantum computer system may be co-located in a data center or located in different data centers. The latency of the communication channel may be selected to optimize cost for a required computer performance.

The invention discloses a microcomputer host aging test method and system, and relates to the technical field of computer performance tests.The microcomputer host aging test method comprises the steps that to-be-tested equipment is connected to a test system, system standby test is conducted, and initial reference data are collected; constructing an aging prediction model and optimizing a model training strategy in combination with course learning and transfer learning; and performing a host preheating test and a high-load test by using AIDA64 based on a prediction result, synchronously operating a Heven Benchmark tool, and testing the graphic processing capability of the computer. The method combines a radial basis function neural network aging prediction model, carries out model training through curriculum learning and transfer learning, intelligently analyzes the CPU / GPU degradation trend, combines a quantum random number generator to generate a random load mode, simulates load fluctuation in an actual application scene, and improves the test trueness. In addition, a BIOS optimization strategy is provided to realize intelligent aging prediction and optimization regulation and control, so that the long-term stability and the service life of the microcomputer host are improved.

The invention discloses an intelligent computer performance testing system based on a Shell script, belongs to the technical field of computer performance testing, and aims to solve the technical problem of how to improve the automation degree of computer performance testing, avoid man-machine interaction and further improve the testing efficiency and accuracy. According to the technical scheme, a test package program installation module is used for triggering and automatically installing a software test package program; the file generation module is used for generating an HPL.Dat file when the mpich software is installed; the file updating module is used for updating the HPL.Dat file generated in the process of installing the software test package program; the execution module is used for transmitting data; the test preparation module is used for providing test information for testing the performance of the computer and processing the test information; and the test item forming module is used for constructing test items according to the separated test information so as to obtain computer system performance test content and record test item information.

The invention provides a computer performance dynamic adjusting system and method based on user operation behaviors, and relates to the technical field of computers. Comprising an event capture module, an operation semantic association module, a system resource optimization module and an adaptive correction module. The event capturing module obtains user operation data and generates an operation event sequence with a timestamp. The operation semantic association module is used for matching an operation event and an operation mode through a nonlinear time axis, and generating a resource demand vector in combination with a window focus and a process stack calling relationship. And the system resource optimization module selects a resource allocation scheme with the lowest power consumption on the basis of an ant colony algorithm under the condition that response time constraints are met, and reallocates resources. And the adaptive correction module adjusts the matching weight of the operation mode by comparing the deviation between the actual response time and the expected response time, and feeds back a corrected matching threshold. The system can dynamically adjust computer performance, improve response speed and reduce power consumption.

The invention relates to a pipeline weld defect intelligent identification method and system, a computing device and a medium, and the method comprises the steps: analyzing an AUT scanning file by using an analytic function, and determining waveform data obtained by scanning a pipeline at different scanning positions according to a scanning direction; marking each waveform data according to defect types, and determining a training set; counting the sample number corresponding to each defect type in the training set, and performing data expansion on the sample number of the defect type of which the sample number is less than a preset value to determine a first target training set; inputting the first target training set into a convolutional neural network for training, and determining an identification network; and according to the identification network, identifying the pipeline welding seam defect. The convolutional neural network is trained through the training set of the data type, the training time is short, the requirement for computer performance is low, and the recognition speed is high.

The invention provides a trusted bare metal server resource partitioning method and system oriented to hardware security extension, and aims to solve the problems of security isolation and efficient utilization of hardware resources in a cloud computing environment. A resource partitioning technology based on hardware security expansion is introduced, and key components such as a security monitor, an isolation domain manager and a trusted execution environment TEE are combined, so that hardware resource fine partitioning and security management of the trusted bare metal server in the multi-tenant environment are realized. The core lies in that shared hardware is partitioned at a natural boundary (such as a core, a memory and I / O equipment), so that a plurality of untrusted client operating systems can run on shared bare metal hardware, meanwhile, performance overhead and potential safety hazards caused by complex virtualization are avoided, functions similar to virtual machines and bare computer performance are realized, and the method has strong isolation performance and is convenient to operate. And meanwhile, safe starting and remote verification are supported.

A component for improving the performance of computers using high speed memories while retaining the flexibility to install only a subset of the memories the computer can support. The component may have a blade portion configured for insertion into the mating interface of connectors forming memory sockets in the computer. The blade portion may include absorptive material selectively placed adjacent conductive elements within the connector so as to damp or prevent undesirable electromagnetic characteristics, such as stub resonances, within memory sockets that are not populated with memories. The component may have absorptive material coupled to signal and ground conductive elements of unpopulated card edge connectors and may have insulative regions that provide isolation between the absorptive material and power conductive elements. The component may be shaped for easy insertion and retention and later removal from the connector to allow a memory card to be later added to the computer.

The invention relates to the technical field of computer system performance and security testing, in particular to a computer performance security testing method and system. The method specifically comprises the steps that performance indexes, behavior characteristics and security event data of a target system are obtained in real time and subjected to standardization processing, clustering modeling is conducted on the behavior characteristics subjected to dimension reduction through a Gaussian mixture model so as to establish a normal behavior pattern cluster, and time sequence analysis is conducted on a behavior sequence in combination with a hidden Markov model so as to recognize a system state transition path; adopting a weighted combination strategy to mix and inject a normal load and an aggressive load, and adjusting an abnormal behavior chain through a disturbance function; constructing directed weighted association between the abnormal event and the performance index based on an event-driven causal performance diagram, quantifying a system risk index and triggering an alarm; outputting performance bottlenecks, security vulnerabilities and optimization suggestions, and updating the knowledge base to optimize subsequent models. According to the invention, deep coupling of performance and safety testing, intelligent scheduling of dynamic loads and interpretable positioning of risk paths are realized.

Estimated and actual processor runtimes improve computer functioning in fairly sharing computing resources. Today's computers and cloud-based services serve many users and many software applications sharing CPU resources. An operating system thus implements a scheduling policy that fairly allocates CPU time. A scheduler thread implements the scheduling policy based on estimated processor runtimes, and actual processor runtimes, associated with tasks. The operating system may maintain running tallies or totals for a user / group / organization based on credits (e.g., the estimated processor runtimes) and / or on penalties (e.g., the actual processor runtimes). The scheduler thread may select tasks for worker threads based on the credits and / or the penalties, thus ensuring that no user / group / organization unfairly consumes CPU time.

The invention relates to a system performance testing method and device, computer equipment and a readable storage medium, and relates to the technical field of computer performance testing. The method comprises the following steps: determining an initial pressure value and a test script of a to-be-tested system; testing the performance of the to-be-tested system under the initial pressure value through the test script to obtain performance index data of the to-be-tested system under the initial pressure value; increasing the initial pressure value to obtain a new pressure value, and returning to the step of testing the performance of the to-be-tested system under the initial pressure value through the test script until an iteration ending condition is met, so as to obtain performance index data of the to-be-tested system under the plurality of pressure values; and according to the performance index data under each pressure value, determining the critical pressure of the to-be-tested system entering the performance bottleneck period. By adopting the method, the test efficiency can be improved.

The present invention relates to the technical field of computer performance testing, and discloses a self-detection method for script performance testing, comprising: obtaining performance test parameters and asset server parameters of a device under test; configuring operation instructions for the asset server in the performance test parameters; running a script performance test file; causing a monitoring module and a package sending module on a performance test press to interact by running the script performance test file, and obtaining the interaction results between the monitoring module and the package sending module; calculating the resources consumed by the package sending module, and configuring and adding resources to the performance test press based on the total resource consumption of users; and recording the resource consumption of the performance test press. The present invention is used for a performance test press, so that the performance test press no longer needs to understand its own performance level in advance, directly simplifying the tester's workflow and the complexity of performance testing, improving the utilization rate of the performance test press, and lowering the threshold for performance testing.

The invention relates to the technical field of quantum computing, in particular to a quantum computer performance monitoring method and device, equipment and a storage medium. The method comprises the steps that a to-be-executed quantum task input into a quantum computer is obtained, quantum entanglement is established between calculation quantum bits and monitoring quantum bits in a target quantum entanglement mode, the target quantum entanglement mode is determined by the to-be-executed quantum task, and the quantum entanglement mode is determined by the to-be-executed quantum task; the calculation quantum bit is a quantum bit used for executing the quantum task to be executed in the quantum computer, and the monitoring quantum bit is used for monitoring the calculation quantum bit; in the process of executing the quantum task to be executed by the calculation quantum bit, measuring the quantum bit state of the monitoring quantum bit to obtain a measurement result; and based on quantum entanglement, determining a performance operation index of the quantum computer according to a measurement result. By the adoption of the scheme, real-time and undisturbed monitoring of the performance of the quantum computer can be achieved.

The invention provides a plant-network-river integrated dispatching simulation calculation method and system based on parallel calculation, and the method comprises the steps: obtaining drainage facility attributes, canal plane distribution and section topography, regional digital elevation and land utilization distribution of a dispatching region, and building an SWMM model; collecting rainfall, surface runoff, and water level, flow and water quality monitoring data in the pipe duct confluence and transmission process of different sessions, and performing parameter calibration on the SWMM model to obtain a calibrated SWMM model; constructing a joint optimization scheduling algorithm model by utilizing a particle swarm algorithm, outputting a drainage facility joint regulation and control rule, inputting the joint regulation and control rule into the calibrated SWMM model, and obtaining a simulation calculation result by adopting a parallel calculation mode; and setting a scheduling rule evaluation index to evaluate the simulation calculation result, and outputting an optimal drainage facility joint regulation and control rule. According to the invention, a CPU parallel computing mode is adopted to realize analog computation of factory-network-river integrated operation scheduling, computer performance is fully exerted, and scheduling decision efficiency is improved.

The invention relates to a model rendering method, a surgery simulation method and a computer readable storage medium, and the method comprises the steps: responding to the interaction between a user and a data model, and determining a user attention region in the data model, the data model comprising voxel data and grid data associated with a preset region of interest; and rendering at least one part of the data model based on the voxel data and the grid data according to the user attention area to obtain a target rendering result. By adopting the method, the reality sense of operation simulation can be improved, and meanwhile, the computer performance requirement required by operation simulation is reduced.

Photonic interposers that enable low-power, high-bandwidth inter-chip (e.g., board-level and / or rack-level) as well as intra-chip communication are described. Described herein are techniques, architectures and processes that improve upon the performance of conventional computers. Some embodiments provide photonic interposers that use photonic tiles, where each tile includes programmable photonic circuits that can be programmed based on the needs of a particular computer architecture. Some tiles are instantiations of a common template tile that are stitched together in a 1D or a 2D arrangement. Some embodiments described herein provide a programmable physical network designed to connect pairs of tiles together with photonic links.

The application belongs to the technical field of computer control, and discloses a notebook computer intelligent heat dissipation control system based on a multi-modal sensor, which comprises the following steps: collecting multi-modal thermal sensing data of a notebook computer; identifying a current running scene type and obtaining user heat dissipation preferences based on the multi-modal thermal sensing data; calculating a thermal trend index of each hardware component of the notebook computer according to historical multi-modal thermal sensing data and the current running scene type; generating a heat dissipation regulation scheme with scene adaptability based on the thermal trend index, the current running scene type and the user heat dissipation preferences; and realizing notebook computer intelligent heat dissipation control in a progressive regulation mode according to the heat dissipation regulation scheme, so that the stability of the notebook computer performance is greatly improved and the hardware service life is prolonged.

The embodiment of the invention provides a memory super-division processing method and system, the memory super-division processing method is applied to a host machine, the host machine runs a plurality of virtual machines, and the method comprises the following steps: determining missing page state data of the plurality of virtual machines in a first historical time period; determining performance loss results of the plurality of virtual machines according to the missing page state data; according to historical cold page data of the multiple virtual machines in a second historical time period, predicted cold page data of the multiple virtual machines in the future time period is determined, the duration of the second historical time period is smaller than or equal to that of the first historical time period, and the duration of the second historical time period is the same as that of the future time period; according to the performance loss result and the predicted cold page data, determining memory super-resolution indexes of the plurality of virtual machines in the future time period; according to the method, the page replacement pressure and the address conversion pressure of the virtual machine are reduced, the performance reduction probability of the host machine is reduced, and the stability of the memory and operation of the host machine is improved.

The present invention relates to the field of artificial intelligence technology, and discloses a computer performance prediction method, comprising the following steps: collecting computer performance data, wherein the computer performance data includes periodic computer performance data and non-periodic computer performance data; fitting the computer performance data using an initial timing analysis model in a preset timing analysis model set to obtain initial parameters of the initial timing analysis model; adjusting the initial parameters of the initial timing analysis model to obtain a timing analysis model; predicting the computer performance data to be predicted using the timing analysis model to obtain a prediction result. The present invention also discloses a computer performance prediction device, equipment, and readable storage medium. The computer performance prediction method provided by the present invention improves the accuracy of computer performance prediction.

The invention discloses a computer performance real-time evaluation method and device based on user experience perception, a storage medium and computer equipment, and the method comprises the steps: obtaining the current operation data of the computer equipment, carrying out the use scene recognition based on the current operation data, and determining a current use scene; obtaining a plurality of user experience perception performance indexes corresponding to the current use scene and the index weight of each user experience perception performance index in a pre-constructed use scene and user experience perception performance weight mapping table; performing performance index data acquisition on the computer equipment according to each user experience perception performance index, and calculating a comprehensive performance score of the computer equipment according to each acquired user experience perception performance index data and the corresponding index weight; and performing real-time performance feedback of the computer equipment according to the comprehensive performance score.

The invention belongs to the technical field of optical processing and detection, and particularly relates to a CGH design method for detecting an axisymmetric complex curved surface, which is characterized in that a half-side phase diagram is binarized according to the characteristics of axisymmetric parts, and the calculation power is saved through symmetric complementation subsequently; accurately determining a stripe curve contour through a Newton iteration method; based on a chord height error control method, adaptive fast coding of CGH stripe positions is realized, and stripe coding accuracy and processing error evaluation consistency are improved. And a Python writing program is applied to complete the generation of a processing file GDSII, and the processing file GDSII is saved in a segmented manner, so that the requirement on the computer performance is reduced.

The invention discloses a game CPU-oriented model identification method and system, and belongs to the technical field of computer performance optimization, and the method comprises the following steps: S1, collecting a real-time performance vector from a CPU core performance monitoring unit; S2, obtaining a predictive load vector from a game engine; s3, adjusting the dynamic learning rate based on the change degree of the predictive load vectors at the current moment and the previous moment; s4, calculating an instantaneous matching degree for each candidate model in a preset candidate CPU micro-architecture model set based on the real-time performance vector, the predictive load vector and a preset reference performance matrix associated with the candidate model; and S5, updating and generating a dynamic confidence score for each candidate model in combination with the confidence, the instantaneous matching degree and the dynamic learning rate of the previous moment, and winning a precious time window for predictive performance optimization of a game engine.

The application belongs to the technical field of computer hardware testing, and discloses a multi-sensor integrated detection dock system for notebook computer performance testing, which comprises a multi-sensor module, a data acquisition and interface module, a main control module and a hardware component. The application has the following remarkable advantages: high integration and improved efficiency; data synchronization precision and improved analysis value; high automation degree and reduction of human error; consistent test conditions and strong result comparability.

The invention discloses a cloud E-sports diskless storage method and system, relates to the technical field of diskless storage, and solves the technical problem that the diskless computer performance is reduced due to the fact that a server side of a diskless computer system is easy to have a single-point fault or a single-point performance bottleneck. The method comprises the following steps: installing a local hard disk on the diskless computer, and setting the local hard disk as a non-system disk; starting the diskless computer, providing read-write capability for the diskless computer through IO service compiled by the diskless server, and performing initial guidance of the diskless computer; a local IO service is automatically started in the operating system, and a network hard disk drive is installed in a local hard disk and configured; and the network hard disk drive redirects the IO service request to a local IO service, and the local IO service accesses a storage cluster of the diskless server. The diskless computer performs data write-back through the local hard disk, the network communication frequency is reduced, meanwhile, the network hard disk drive redirects the IO request to the local IO service, delay is not prone to occurring, and the performance of the diskless computer is ensured.

Techniques to help reduce latency and improve computer performance including managing latency between client computers over a network with server computers including determining configurable time period, communicating quote data to client computers, determining most recent quote data from a cache and determining whether to execute quote data based on quote version data and time data associated with the quote data and based on the configurable time period.

The present application provides a map data processing method, device, electronic device, and storage medium. The method includes: determining the distance between each grid node in the first-level grid of the map and the viewing position; determining whether the grid node is an aggregatable node based on the distance between each grid node in the first-level grid and the viewing position; if so, displaying a target aggregation point at the location of the aggregatable node on the map; if not, obtaining each grid subnode of the grid node, and displaying the target aggregation point or obtaining the next-level grid subnode of the grid subnode based on the distance between the grid subnode and the viewing position, and looping through these steps until the current grid subnode is the last-level grid subnode. The method can calculate aggregated content by determining the distance between the grid node and the viewing position, thereby reducing computing pressure, lowering computer performance loss, and avoiding lag issues during rendering.

This invention discloses a computer performance data acquisition method and system, relating to the field of computer data processing technology. Based on the load prediction value Ldp, the system automatically adjusts its operating rhythm. When the device is under high pressure, the sampling adjustment coefficient Frs is suppressed due to the increase in the acquisition overhead value Coi, thereby dynamically lengthening the sampling interval Del, thus preventing the acquisition behavior from exacerbating congestion. When the device is idle, the processing utilization Cpuu, memory utilization Memu, and thread switching rate Ths remain at low values, and the load prediction value Ldp derived from the trend base value Tbs and the acquisition overhead value Coi is low, causing the sampling interval Del to be actively shortened. This allows for early capture even when the user is not operating but background programs are gradually increasing. Traditional fixed-frequency acquisition methods often fail to identify performance degradation inflection points in a timely manner, while the continuous accumulation of the trend base value Tbs triggers an increase in the sampling frequency at an early stage.

The invention discloses a performance monitoring method and device for an image-text mixed data set, a storage medium and a product, and relates to the technical field of computer performance monitoring, the method is applied to a client, the client comprises a to-be-monitored browser, and the method comprises the steps that in response to a starting instruction of running an image-text mixed data set page by the browser, the image-text mixed data set page is started; collecting a performance log when the browser runs the image-text mixed data set page; the collected performance logs are uploaded to a server in batches, so that the server analyzes the performance logs to obtain a performance analysis result of the browser, and a corresponding optimization strategy is determined based on the performance analysis result; and obtaining an optimization strategy, and adjusting the operation mode of the browser and the display parameters of the image-text mixed data set based on the optimization strategy. According to the method and the device, the performance of the browser for processing the image-text mixed data set can be monitored, so that the performance of the browser is improved.

The invention discloses computer performance volatility prediction. The ML model is trained to learn a relationship between an empirical distribution indicating the identifier and an empirical distribution of a volatility fiducial associated with executing the application on a first computer system having a first configuration. At least one empirical distribution of the first volatility fiducial associated with the application is assigned to the ML model. Output information indicative of at least one indication identifier associated with the first volatility reference is received from the ML model.

The present invention discloses a minicomputer performance optimization method and system based on dynamic regulation, which specifically relates to the field of dynamic regulation, including S1: dividing time feature text, S2: obtaining key text, S3: preprocessing key text, S4: analyzing key text, S5: comprehensive analysis, S6: optimizing performance, S7: human-computer interaction. Through the division of time feature text, a first performance key text and a second performance key text are obtained, and the key text is preprocessed to obtain keyword groups corresponding to the key texts, so as to obtain a first performance evaluation value and a second performance evaluation value through a minicomputer performance intelligent analysis model; based on the first performance keyword group and the second performance keyword group, a comprehensive performance text output value is obtained, and a comprehensive performance evaluation analysis model is constructed to obtain a comprehensive performance evaluation value, so that in the minicomputer optimization process, different optimization effects can be achieved according to the comprehensive performance evaluation value.