68 results about "Program optimization" patented technology

The invention relates to the technical field of GPU (Graphics Processing Unit), in particular to a GPU program optimization method based on a CUDA (Compute Unified Device Architecture) parallel environment, which comprises the following steps: acquiring a task request sent by a target GPU program, and carrying out priority queue classification on the task request based on a priority coefficient of the task request so as to divide the task request into different priority queues; the activity coefficient of each priority queue is calculated based on the delays of the different priority queues, resource scheduling is carried out on each priority queue through each calculation node in the calculation cluster based on the activity coefficient of each priority queue, and each calculation node is composed of a CPU and a GPU. According to the method, the task requests are subjected to priority queue classification, so that the tasks with high priorities can be preferentially processed, the response speed and efficiency of the whole system are improved, the tasks with different priorities can be effectively managed through task priority queue classification, resource conflicts are avoided, and the processing capacity of key tasks is improved.

The invention relates to a control method for an electroplating production line with an optimized PLC program. A multi-dimensional data analysis model is adopted, key parameters such as electroplating time, hanger circulation speed and bath occupation condition are comprehensively considered, and a process time relevance matrix is constructed; self-adaptive rhythm adjustment is carried out in the PLC, and the transmission rhythm is dynamically adjusted to enable circulation among the process nodes to be balanced; a multi-channel data acquisition system is connected to the PLC end, and the temperature, the current density, the voltage fluctuation, the plating solution concentration and the pH value key variables of the plating solution are monitored; a Bayesian optimization algorithm is adopted, electroplating process parameters are calculated based on historical data and real-time data, and an output control value of a PLC is dynamically adjusted; carrying out sampling analysis on the current consumption mode of each electroplating bath by adopting a PLC (Programmable Logic Controller), and establishing a power demand prediction model; current output is distributed through a dynamic power distribution algorithm, so that power consumption is kept in an optimal state; and in combination with a peak load reduction strategy, power supply is optimized in low load.

The invention provides a method for optimizing system security vulnerability management based on an extension program. The method can be applied to the field of information security or the field of artificial intelligence. The method comprises the following steps: in response to a business demand of developing an application system, collecting a code under editing in an integrated development environment in real time; scanning security vulnerabilities of the codes under editing through a customized extension program, analyzing and comparing the codes under editing according to rules in a rule base, and identifying potential security vulnerabilities, the customized extension program being integrated in an integrated development environment, and the rule base being built in the customized extension program; in response to the scanned security vulnerability, obtaining a repair suggestion for the security vulnerability by using a pre-trained vulnerability management model according to the compiled code associated with the security vulnerability; and on the basis of the repair suggestion, adjusting the code under editing so as to repair the security vulnerability. The invention further provides a device and equipment for optimizing system security vulnerability management based on the extension program, a storage medium and a program product.

The invention relates to the technical field of industrial internet, in particular to an automatic scheduling system for multi-chip parallel burning, which is characterized in that a program optimization and deployment module dynamically adapts a basic program according to hardware resources of a target equipment cluster and process parameters of chips, generates an efficient optimized burning program, and sends the efficient optimized burning program to a server; verifying the digital digest through an integrated block chain network and performing safe deployment; the intelligent scheduling decision module utilizes a dynamic digital twinborn model to perceive the equipment state and deployed optimization program characteristics in real time, and intelligently generates a global burning task optimal allocation scheme and a scheduling instruction; the cooperative control module compares actual efficiency with expected efficiency in real time, quantifies deviation and then feeds back the deviation to the reinforcement learning scheduling engine, and the engine automatically adjusts and continuously iteratively optimizes the overall scheduling strategy. According to the invention, the scheduling efficiency of multi-chip parallel burning can be improved.

The invention provides a GPU program optimization method in a parallel environment, a plurality of target models are configured in a GPU cluster for parallel training, and the method comprises the following steps: performing strategy configuration and memory bottleneck pre-judgment on parallel training configuration of the target models; carrying out throughput optimization through parallel strategy combination and instruction-level performance monitoring by utilizing a pre-judgment result; kernel re-optimization is carried out on an instruction level bottleneck appearing in the optimization process, so that the model training efficiency and the GPU instruction execution efficiency are synchronously improved.

The embodiment of the invention provides an application program optimization method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting resource calling data of an application program on user equipment; identifying a to-be-optimized resource set based on the resource calling data; executing optimization processing on the to-be-optimized resource set to obtain an optimized target application program; wherein the optimization processing comprises resource removal or resource relocation. Compared with a traditional static analysis method, the method has the advantages that through a data analysis mode driven by user behaviors, the risk of function missing possibly caused by blind deletion of resources is avoided, and more accurate and safer application program optimization is realized. Besides, for the resources which are used at low frequency but are still necessary to be reserved, the optimization of the initial packet volume is realized while the functional integrity is maintained through a processing mode of resource relocation instead of simple deletion, and the relationship between the user experience and the resource efficiency is balanced.

The invention provides a collaborative interval management conversion program optimization method based on flight demand uncertainty. The method comprises the following steps: determining an uncertainty variable of a collaborative interval management conversion program CMCP optimization problem; estimating probability density function key parameters of normal distribution of the uncertainty variables according to historical data; constructing a CMCP opportunity constrained programming model and equivalent transformation thereof; and solving the converted CMCP opportunity constraint programming model based on a particle swarm algorithm. According to the method, the flight demand uncertainty factor, namely the uncertainty of the flight point passing time, is considered. Under the condition that the actual flight passing time is uncertain and interfered, the flight operation based on the optimization result can keep good airspace performance, so that the actual execution effect of the flight plan cannot be seriously fluctuated due to the uncertainty of the flight passing time.

The invention relates to a digital twin virtual debugging method for jet printing manufacturing control optimization, and belongs to the technical field related to intelligent manufacturing and industrial control. Comprising the following steps: configuring a control logic program for each equipment sub-module in a jet printing manufacturing equipment twin model through an equipment master controller, and writing the control logic program into a corresponding virtual controller; establishing communication connection between each virtual controller and the twin model, verifying a control logic program in the virtual controller, and verifying and optimizing the control logic program through general control; and inputting each optimized control logic program into the entity controller of the corresponding equipment sub-module, sending a control instruction to the entity controller corresponding to the equipment sub-module of which the current motion is to be verified through general control, driving the equipment sub-module to execute an action, optimizing the control logic program in the current entity controller through the general control, and verifying the current motion of the equipment sub-module. And through multi-round program optimization, a control program of the jet printing manufacturing equipment is obtained. The debugging time and cost of the ink-jet printing equipment can be reduced.

A system identifies an ordered data structure that enables a computer to follow a particular order of execution for solving blocks of equations that collectively constitute a simulation model. The system uses the ordered data structure to identify a subset of the blocks of equations that require optimizing by an optimizer program and / or a remaining set of blocks of equations which can be solved without optimization by the optimizer program. The optimizer program optimizes only the subset of the blocks of equations that require optimizing by the optimizer program, thereby reducing an amount of computer resources required for optimization, by varying any blocks of equations declared as independent variables in an iterative process until the optimizer program generates optimized values that converge on a solution. Using the optimized values, a solver program executes each calculation only once when sequentially solving the remaining set of the blocks of equations.

The invention belongs to the field of computer system construction, and particularly relates to a CPU bottleneck analysis model based on a performance counter. The technical problems that in a method for discovering the performance bottleneck of the CPU by building a CPI stack in the prior art, average delay evaluation of failure events needed by performance evaluation is limited, failure delay is difficult to fully expose due to the streamline technology of a modern processor, and therefore discovering of the performance bottleneck of the CPU by the CPI stack is affected are solved. According to the method, each clock cycle pause of a program instruction is allocated to a corresponding failure event, and a relationship between the instruction pause and the failure event is obtained by extracting a key performance signal in a program execution process based on an interactive analogy model, so that a performance model is constructed and is used for guiding program optimization and processor hardware iteration. The CPIstack algorithm constructed by using the performance counter can be deployed on a prototype verification platform, and the performance of the processor can be accurately evaluated.

The invention discloses a GPU resource aware matrix multiplication parallel performance analysis model construction method, which relates to the technical field of high-performance calculation, depends on the Roofline principle, combines a bandwidth model, a resource load model and an instruction dependence model to construct a performance analysis model, and is successfully applied to a matrix multiplication scene. And the parallel performance quantification under the matrix multiplication application of resource awareness is realized. The method is not limited by a platform, resource awareness can be achieved, maximized resource use and parameter setting of optimized performance can be distinguished through a performance analysis model in a matrix multiplication scene, and a foundation is laid for follow-up parallel program optimization work; the hardware parameters used in the method are completely based on the GPU hardware parameters which can be obtained publicly, so that non-GPU professionals can also use the model to evaluate the performance of the program.

The invention discloses a control flow graph representation method and system for obtaining a basic block calling relation of an HIP kernel function, and the method comprises the steps: extracting the kernel function of an HIP program, compiling the kernel function into an LLVM IR intermediate code, and dividing the kernel function into a plurality of basic blocks; a unique serial number is distributed to each basic block, and a new edge basic block is inserted into the jump edge to represent the calling relation; generating a kernel function control flow diagram of a basic block level; the LLVM is used for instrumenting Pass, and instrumentation is carried out on the newly-added edge basic blocks; the method comprises the following steps: designing two lightweight thread instrumentation modes to reduce the instrumentation overhead, namely ProfileCTA and ProfileWavefront; the method comprises the following steps of: operating on a domestic DCU (Data Communication Unit) platform by adopting a compiling process of combining instrumentation of an equipment end and a host end, collecting calling times among basic blocks, taking dynamic information as an edge weight of CFG, and finally generating a basic-block-level HIP program kernel function CFG with the dynamic information. According to the method, the instrumentation overhead is effectively reduced, the obtaining efficiency of the dynamic calling relation is improved, and powerful support is provided for high-performance calculation and program optimization.

The invention discloses a program compiling device and method, and belongs to the technical field of computers. The device comprises a receiving module used for receiving a log collected by an instrumentation program in the running process of a target program, the instrumentation program is a part of the target program, and the log comprises popularity data of at least one function in the target program; and the compiling module is used for performing biased compiling on the target program based on the popularity data of the at least one function to obtain an updated target program, and the biased compiling comprises compiling of a biased performance optimization operation or compiling of a biased code area compression operation. In this way, the program can be optimized and upgraded better, and user requirements are met.

The embodiment of the invention provides an application program optimization method and electronic equipment, and relates to the technical field of computers. The problem that after upgrading and restarting, all application programs cannot be executed through machine codes within a long time is solved. According to the specific scheme, a first operating system runs; an upgrade installation package is obtained, and the upgrade installation package is used for upgrading the operating system; the operation system upgrading comprises the steps that an upgrading installation package is installed, a first number of first applications are optimized and compiled, and the first number is smaller than the total number of the application programs; and in response to completion of optimized compiling of the first number of first applications, triggering restart.

The invention discloses a container resource quota recommendation method for Java program optimization, and belongs to the technical field of computers. The method comprises the following steps: acquiring monitoring data; the monitoring data comprises a CPU utilization rate and a memory usage amount; performing CPU resource quota recommendation according to the CPU utilization rate; and performing memory resource quota recommendation according to the memory usage amount. According to the method, the peak value of the memory usage amount of the JVM heap is accurately predicted through the LSTM model on the basis of the operation characteristics and the actual monitoring data of the Java program, and a more accurate CPU and memory quota recommendation method is provided. Compared with a traditional method, the resource demand of the Java program can be predicted more accurately, the problems of waste and insufficiency of resources are avoided, and the resource utilization rate of the Kubernetes cluster is remarkably improved.

In variants, a program optimization method can include: receiving a program; determining a set of proxy inputs for the program; generating a set of intermediate traces for the program; and generating a set of execution traces for the program, wherein the set of execution traces can include executor fusions associated with device kernels for hardware accelerators. During runtime, program results can be computed by executing an execution trace instead of executing the program.

Provided is an application optimization method and an electronic device supporting the same. According to an example embodiment, the application optimization method may include: determining whether a condition set with respect to a duration of an idle state of the electronic device is satisfied, selecting an application for which application optimization is to be performed based on an application usage record of a user of the electronic device in response to the set condition being satisfied, and generating an optimized application by performing the application optimization in the background for the selected application.

The invention provides a dynamic instruction replacement method and device, equipment and a storage medium, and the method comprises the steps: determining a to-be-optimized instruction group according to instruction operation information of a plurality of instruction groups, and obtaining a replacement instruction group corresponding to the to-be-optimized instruction group, the performance of the replacement instruction group is better than that of the to-be-optimized instruction group, and the performance of the replacement instruction group is better than that of the to-be-optimized instruction group; and storing the replacement instruction group to a pre-occupied virtual address field, if the to-be-processed current instruction stream comprises the to-be-optimized instruction group, skipping to the virtual address field to execute the replacement instruction group when executing to the to-be-optimized instruction group in the current instruction stream, and skipping to the current instruction stream after the execution of the replacement instruction group is finished, and executing instructions behind the instruction group to be optimized. According to the method and the device, function-level instruction replacement is realized, the program optimization cost is reduced, and the program running efficiency can be effectively improved.

The invention provides a particle program optimization method based on a Shenwei architecture. The method comprises the following steps: analyzing program hotspots, finding and calculating a hotspot function, and optimizing the function by using five means of particle control, step number parameter control, data classification transmission, function expansion and function inline by utilizing the advantages of an SW26010pro architecture; the execution efficiency of the particle program is improved, the computing performance of the Shenwei architecture is fully played, and rapid and effective operation of the large-scale particle computing program is achieved.

The application relates to an automatic program optimization method and device based on a flow network generation model and a storage medium, wherein the method comprises the following steps: S1, an initial tensor program is acquired, a plurality of candidate tensor programs with the same logical function are obtained through calculation graph extraction, subgraph segmentation and transformation based on the acquired initial tensor program, and a data set composed of a plurality of samples is constructed based on the obtained candidate tensor programs, wherein the sample comprises a binary tuple composed of a calculation subgraph and a candidate tensor program, and the hardware execution time corresponding to the binary tuple; S2, a plurality of samples are selected from the data set, and a GFlowNet sampling model is trained offline; and S3, the trained GFlowNet sampling model is used to optimize a program to be optimized. Compared with the prior art, the GFlowNet adopts a non-iterative probabilistic sampling strategy, generates a plurality of high-performance programs, apportions the sampling overhead from one mode to another mode, and accelerates the convergence speed.

A system identifies an ordered data structure that enables a computer to follow a particular order of execution for solving blocks of equations that collectively constitute a simulation model. The system uses the ordered data structure to identify a subset of the blocks of equations that require optimizing by an optimizer program and / or a remaining set of blocks of equations which can be solved without optimization by the optimizer program. The optimizer program optimizes only the subset of the blocks of equations that require optimizing by the optimizer program, thereby reducing an amount of computer resources required for optimization, by varying any blocks of equations declared as independent variables in an iterative process until the optimizer program generates optimized values that converge on a solution. Using the optimized values, a solver program executes each calculation only once when sequentially solving the remaining set of the blocks of equations.

The application relates to the technical field of program optimization, and particularly discloses a small program code volume reduction method and device, a storage medium and a computer device. The method comprises the following steps: in response to a small program code volume reduction instruction, determining a target small program to be subjected to volume reduction; acquiring a global configuration file of the target small program, and parsing declared valid page paths from the global configuration file; scanning an engineering directory corresponding to the target small program, and identifying a plurality of page directories contained in the engineering directory; comparing each page directory with the declared valid page paths respectively, so as to screen out redundant page directories not contained in the valid page paths from the plurality of page directories; and deleting the redundant page directories and all files under the redundant page directories, so as to obtain a target small program after code reduction.

The invention discloses a converged media program list arrangement system and a generation method, and belongs to the technical field of media content management and intelligent scheduling. The system comprises a content acquisition module, a feature extraction module, a user portrait and platform model module, a program optimization and arrangement module, an intelligent conflict detection module, a self-adaptive generation module and a feedback optimization module. Unified management of program resources is realized through multi-source content collection and semantic tagging analysis; a multi-objective optimization model is constructed based on the user portrait and the platform strategy, and program lists adapted to different terminals are automatically generated; and dynamically adjusting a programming result by utilizing a conflict detection and self-learning feedback mechanism. According to the method, the intelligent level of convergence media program management can be remarkably improved, the cross-platform content distribution efficiency is optimized, and automatic generation and accurate pushing of the program list are realized.

Embodiments of the invention disclose an instruction fusion method and apparatus, an electronic device, a storage medium and a program product. The method comprises the steps of obtaining a to-be-optimized program; when it is determined that all instructions in the to-be-optimized program belong to the same basic block and the instructions with the dependency relationship in the to-be-optimized program are adjacently arranged, all continuous instruction sequences in the to-be-optimized program are obtained, to-be-fused instruction sequences are determined in all the continuous instruction sequences, and each set of to-be-fused instruction sequences is replaced with a corresponding fusion instruction; when it is determined that all the instructions in the to-be-optimized program do not belong to the same basic block or the instructions with the dependency relationship in the to-be-optimized program are not adjacently arranged, obtaining candidate instructions in the to-be-optimized program, determining to-be-fused instructions in the candidate instructions according to the fixed value-use chains corresponding to the candidate instructions, and fusing the to-be-fused instructions in the to-be-optimized program according to the determined to-be-fused instructions in the to-be-optimized program. And the target instruction sequence corresponding to each instruction to be fused is replaced with the corresponding fusion instruction, so that the program optimization efficiency and the program optimization capability are balanced.

The invention relates to an automatic program optimization method and system for synthesizing and eliminating an intermediate data structure by utilizing an induction program. The method comprises the following steps: acquiring a low-efficiency program which is input by a user and contains an intermediate data structure, and appointing the intermediate data structure which needs to be eliminated; a specified intermediate data structure is replaced by a scalar type, and related program fragments in the original program are rewritten using efficient program fragments of constant time complexity. The invention provides a novel induction program synthesis method aiming at the problem of eliminating an intermediate data structure, the induction program synthesis problem can be efficiently decomposed into simpler subtasks, so that the confronted efficiency problem is overcome, and the method has stronger expression ability than an existing fusion method, and can be widely applied to the field of data fusion. And the time for a programmer to carry out efficient system development can be greatly reduced.

According to an implementation, a computer-implemented method to determine an optimal configuration of a benchmark program is proposed. The method includes iteratively selecting a unique parameter set from a parameter space, each parameter set corresponding to a unique configuration of the benchmark program; running the benchmark program as configured for each parameter set at least once; determining an evaluation score for each parameter set from one or more runs using an evaluation heuristic; recording an optimal parameter set having a best evaluation score; and configuring the benchmark program based on the optimal parameter set.

A program optimization device according to the present invention: detects, from a machining program, a section in which a cutting command for synchronizing rotation of a main shaft and movement of a feed shaft and a non-cutting command are continuous; acquires, from the machining program, a physical quantity for optimizing the detected section; calculates a command value for converting the non-cutting command into linear interpolation on the basis of the physical quantity; converts the non-cutting command into linear interpolation; adds the command value to the linear interpolation; and outputs, as an optimized machining program, a machining program with less electric energy consumption among the machining programs before conversion and after conversion.

The invention relates to an automatic program optimization method and device for an application program, computer equipment and a storage medium. The automatic program optimization method comprises the following steps: acquiring execution information and initial performance data of each instruction in a plurality of instructions when the application program runs; determining a hotspot instruction according to the execution information of each instruction in the plurality of instructions; obtaining an instruction type of the hotspot instruction, judging an instruction optimization mode corresponding to the instruction type, and if the instruction optimization mode is judged to be based on the configuration template, obtaining a matched target optimization template from a preset template library according to the instruction type; performing code optimization on the hotspot instruction according to an optimization strategy and a code mode configured in the target optimization template to generate an optimization code of the hotspot instruction; and performing program optimization on the application program according to the optimization code and the initial performance data of the application program. According to the method, the accuracy, the automation degree and the efficiency of software performance optimization are improved.

The invention discloses a real-time monitoring system for a dry net cleaning vacuum valve. The real-time monitoring system comprises a detection module, an alarm module, a feedback module, a program optimization module, a bracket structure and a data storage module, according to the invention, a dry net cleaning program is optimized by using off-machine limiting and self-processing of the fixing bracket, and the real-time use condition of the vacuum valve is efficiently detected without cost. And the conditions of wastage reduction and dry screen printing caused by blockage of the vacuum valve are effectively avoided, and the quality of finished paper is improved. Meanwhile, by adding real-time feedback and alarm functions on a DCS picture, the abnormity of the vacuum valve can be found in time, the failure rate is reduced, the workload of personnel is reduced, and the market competitiveness of a company is further improved. In addition, the detachable support facilitates later maintenance, the troubleshooting time is shortened, and the data storage module facilitates later analysis and summarization of equipment operation conditions.

The invention discloses a tensor program functionalization method, tensor program functionalization equipment and a tensor program product. The method comprises the following steps: acquiring a tensor program, and constructing a graph-level intermediate representation program of the tensor program; performing mutation rewriting and tensor version relation labeling on the graph-level intermediate representation program based on a memory dependency graph and an immutable operator of the graph-level intermediate representation program to obtain a rewritten graph-level intermediate representation program; the immutable operator is used for replacing a mutation operator in a graph-level intermediate representation program, and a new version tensor output by the immutable operator and an input source tensor have independent memories; and performing program optimization on the rewritten graph-level intermediate representation program to obtain a functional tensor intermediate representation program based on the static single assignment. The Graph-Level IR program is combined with the static single assignment SSA, so that the side effect of tensor mutation in the Graph-Level IR program is thoroughly eliminated, and the optimization performance of a deep learning compiler on the tensor program is improved.