Calculation power operation task no-load method and device of intelligent calculation center

Abstract

The invention provides a computing power operation task no-load method and device of an intelligent computing center. The method comprises the steps of obtaining a computing power operation task data recovery task to be completed; when the number of the obtained computing power operation task data recovery tasks to be completed is 0, it is confirmed that the main thread is in a computing power operation task no-load state, the number of created working threads is set to be 0, and the working threads are used for executing the computing power operation task data recovery tasks to be completed; according to the fact that the number of the to-be-completed computing power operation task data recovery tasks is 0, it is confirmed that the number of completed computing power operation task data recovery tasks is larger than or equal to the to-be-completed computing power operation task data recovery tasks, and it is confirmed that all working threads exit; and exiting the main thread. According to the invention, the method for no-load operation of the computing power operation task of the intelligent computing center is provided, unnecessary consumption of computing power resources is avoided, and the robustness and stability of the intelligent computing center are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent computing centers, smart computing centers and computing power infrastructure, and in particular to a method and device for idling computing power operation tasks in an intelligent computing center. Background Art

[0002] With the rapid development of artificial intelligence technology, "intelligent computing centers" and "intelligent computing centers" have emerged.

[0003] An "Intelligent Computing Center" is a facility that uses large-scale heterogeneous computing resources, including general-purpose and intelligent computing power, to provide the computing power, data, and algorithms required for AI applications (such as AI deep learning model development, model training, and model inference). The Intelligent Computing Center encompasses facilities, hardware, and software, and provides a full stack of capabilities, from bottom-level computing power to top-level application enablement.

[0004] “Intelligent Computing Center” includes but is not limited to “Smart Computing Center”.

[0005] "Intelligent Computing Center" refers to an artificial intelligence computing center. It is a type of computing power infrastructure that is based on artificial intelligence theory, adopts artificial intelligence computing architecture, and provides computing power services, data services, and algorithm services required for artificial intelligence applications.

[0006] "Computing power" is the core of "intelligent computing center" and "intelligent computing center". It is the ability of computer equipment or computing / data center to process information. It is the ability of computer hardware and software to work together to perform certain computing needs. It is the computing power to achieve target result output by processing information data. It is a new type of productivity that integrates information computing power, network carrying capacity, and data storage capacity. It mainly provides services to society through computing power infrastructure.

[0007] Since the emergence of intelligent computing centers, there has been a lack of methods to idle computing power tasks in intelligent computing centers, which leads to unnecessary consumption of computing resources and seriously affects the robustness and stability of intelligent computing centers. Therefore, how to achieve idle computing power tasks in intelligent computing centers is an urgent problem to be solved. Summary of the Invention

[0008] The present invention provides a method and device for idling computing power operation tasks of an intelligent computing center, so as to solve the problem that there has been a lack of a method for idling computing power operation tasks of an intelligent computing center since the emergence of the intelligent computing center.

[0009] In order to solve the above-mentioned technical problems, the present invention is achieved as follows:

[0010] In a first aspect, the present invention provides a method for idling computing tasks in an intelligent computing center, which is applied to a main thread and includes:

[0011] Step S1: Obtain the data recovery task of the computing power operation task to be completed;

[0012] Step S2: When the number of the computing power running task data recovery tasks to be completed is 0, confirm that the main thread is in a computing power running task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the computing power running task data recovery tasks to be completed;

[0013] Step S3: according to the number of the to-be-completed computing power running task data recovery tasks being 0, confirming that the number of completed computing power running task data recovery tasks is greater than or equal to the to-be-completed computing power running task data recovery tasks, and confirming that all worker threads have exited;

[0014] Step S4: Exit the main thread.

[0015] Optionally, before step S1, the method further includes:

[0016] Step S0: Initialize the number of completed computing power running task data recovery tasks; and determine whether the task container sent by the user is valid, wherein the task container includes the computing power running task data recovery task; if the task container is invalid, directly exit the main thread; if the task container is valid, enter step S1.

[0017] Optionally, step S2 includes:

[0018] Step S21: confirming that the main thread is in an idle state for computing task execution and setting the number of created worker threads to 0 are printed in the workbench and / or work log.

[0019] Optionally, step S21 includes:

[0020] Step S211: Analyze and visualize the records in the workbench and / or work log in the form of charts or text.

[0021] In a second aspect, the present invention provides a main thread, comprising:

[0022] The acquisition module is used to obtain the data recovery tasks of the computing power running tasks to be completed;

[0023] A first processing module is configured to, when the number of the to-be-completed computing power operation task data recovery tasks obtained is 0, confirm that the main thread is in a computing power operation task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the to-be-completed computing power operation task data recovery tasks;

[0024] A second processing module is used to confirm that the number of completed computing power running task data recovery tasks is greater than or equal to the computing power running task data recovery tasks to be completed, and confirm that all working threads have exited;

[0025] The exit module is used to exit the main thread.

[0026] Optionally, also include:

[0027] An initialization module is used to initialize the number of completed computing power operation task data recovery tasks; and to determine whether the task container sent by the user is valid, wherein the task container includes the computing power operation task data recovery task; if the task container is invalid, the main thread is directly exited; if the task container is valid, step S1 is entered.

[0028] Optionally, the first processing module includes:

[0029] The first processing submodule is used to print the execution status of confirming that the main thread is in an idle state for computing power running tasks and setting the number of created working threads to 0 in the workbench and / or work log.

[0030] Optionally, the first processing module includes:

[0031] The second processing submodule is used to analyze and visualize the records in the workbench and / or work log in the form of charts or text.

[0032] In a third aspect, the present invention provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps in the method for idling computing power tasks of an intelligent computing center as described in any one of the first aspects are implemented.

[0033] In a fourth aspect, the present invention provides a readable storage medium storing a program or instruction. When the program or instruction is executed by a processor, the steps in the method for idling computing power tasks of an intelligent computing center as described in any one of the first aspects are implemented.

[0034] In a fifth aspect, the present invention provides a computer program product comprising computer instructions, which, when executed by a processor, implement the steps of the method for idling computing power tasks in an intelligent computing center as described in any one of the first aspects.

[0035] In the present invention, a data recovery task of computing power running tasks to be completed is obtained; when the number of the acquired data recovery tasks of computing power running tasks to be completed is 0, the main thread is confirmed to be in a computing power running task no-load state, and the number of created worker threads is set to 0, wherein the worker thread is used to execute the computing power running task data recovery task to be completed; based on the number of the computing power running task data recovery tasks to be completed being 0, it is confirmed that the number of completed computing power running task data recovery tasks is greater than or equal to the computing power running task data recovery tasks to be completed, and it is confirmed that all worker threads have exited; and the main thread is exited. A method for no-loading the computing power running tasks of an intelligent computing center is provided, which avoids unnecessary consumption of computing power resources, improves the robustness and stability of the intelligent computing center, and solves the problem of the lack of a method for no-loading the computing power running tasks of an intelligent computing center since the emergence of the intelligent computing center. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0037] Figure 1 This is a flowchart of a method for idling computing tasks in an intelligent computing center provided by the present invention and applied to a main thread;

[0038] Figure 2 This is a structural diagram of a thread pool of a computing power running task no-load method of an intelligent computing center provided by the present invention;

[0039] Figure 3 This is a general flow chart of the application of the computing power running task no-load method of the intelligent computing center provided by the present invention to the main thread;

[0040] Figure 4 This is a structural diagram of a main thread provided by the present invention;

[0041] Figure 5 It is a structural schematic diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0042] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0043] First, the technical terms involved in the present invention are briefly explained below.

[0044] The "computing power" mentioned in the present invention refers to: the ability of computer equipment or computing / data centers to process information, the ability of computer hardware and software to work together to execute certain computing requirements, and the computing power to achieve target result output by processing information data. It is a new type of productivity that integrates information computing power, network carrying capacity, and data storage capacity, and mainly provides services to society through computing power infrastructure.

[0045] The "computing power" (CP) mentioned in the present invention refers to: the ability of a data center server to process data and output results. It is a comprehensive indicator to measure the computing power of a data center, including general computing power, super computing power and intelligent computing power. The commonly used unit of measurement is the number of floating-point operations performed per second (FLOPS, 1EFLOPS=10^18FLOPS). The larger the value, the stronger the comprehensive computing power. According to calculations, 1EFLOPS is approximately the computing power output of 5 Tianhe-2A or 500,000 mainstream server CPUs or 2 million mainstream notebooks. The calculation formula is: CP=CP 通用 +CP 智能 +CP 超级 .

[0046] The "carrying capacity" (Network Power, NP) mentioned in the present invention refers to: it is the performance of the data transmission capability of the computing power facility, which includes comprehensive capabilities such as network architecture, network bandwidth, transmission latency, intelligent management and scheduling, etc. It involves network transmission within and between data centers, and is a comprehensive indicator for measuring network transmission scheduling capabilities.

[0047] The "Storage Power" (SP) described in this invention refers to the comprehensive capabilities of a data center in terms of data storage capacity, performance, security and reliability, and environmental friendliness. It is a comprehensive indicator for measuring a data center's data storage capacity, encompassing both external storage devices such as storage arrays and server-internal storage. Storage capacity is commonly measured in exabytes (EB, 1EB = 2^60 bytes), while performance is commonly measured in IOPS / TB (Input / Output Operations Per Second / TB). Disaster recovery ratio is a key indicator of security and reliability.

[0048] The "computing power infrastructure" mentioned in the present invention refers to a new type of information infrastructure that integrates information computing power, network carrying capacity, and data storage capacity, and can realize the centralized calculation, storage, transmission and application of information.

[0049] The "new information infrastructure" mentioned in the present invention refers to: mainly including network infrastructure such as 5G networks, fiber-optic broadband networks, backbone networks, international communication networks, satellite Internet, computing power infrastructure such as data centers, general computing power centers, intelligent computing centers, supercomputing centers, and new technology facilities such as artificial intelligence, blockchain, and quantum computing.

[0050] The "computing power" mentioned in the present invention includes: general computing power, intelligent computing power and super computing power.

[0051] The "general computing power" mentioned in the present invention refers to the computing power provided by servers based on CPU (Central Processing Unit) chips, which is used to support basic general computing such as cloud computing and edge computing.

[0052] The "intelligent computing power" mentioned in this invention refers to: a computing platform based on specialized chips such as GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array), and ASIC (Application Specific Integrated Circuit) for various innovative artificial intelligence applications, such as natural language processing and machine vision.

[0053] The "supercomputing power" mentioned in the present invention refers to the computing power provided by high-performance computing clusters such as supercomputers. It utilizes the centralized computing resources of multiple computer systems working in parallel and uses a dedicated operating system to handle extremely complex or data-intensive problems. It is mainly used for calculations in cutting-edge scientific fields, such as planetary simulation, drug molecule design, genetic analysis, etc.

[0054] The "intelligent computing center" described in this article refers to a facility that provides the computing power, data, and algorithms required for artificial intelligence applications (such as AI deep learning model development, model training, and model inference) by utilizing large-scale heterogeneous computing resources, including general-purpose computing power (CPU) and intelligent computing power (GPU, FPGA, ASIC, etc.). The intelligent computing center encompasses facilities, hardware, and software, and can provide a full stack of capabilities, from bottom-level computing power to top-level application enablement.

[0055] The "intelligent computing center" mentioned in the present invention includes but is not limited to the "intelligent computing center".

[0056] The "intelligent computing center" mentioned in the present invention is an artificial intelligence computing center, which is a type of computing power infrastructure based on artificial intelligence theory, adopts artificial intelligence computing architecture, and provides computing power services, data services and algorithm services required for artificial intelligence applications.

[0057] The "computing power center" mentioned in the present invention refers to: a facility that is mainly composed of infrastructure such as wind, fire, water, electricity, and IT hardware and software equipment, and has computing power, transportation capacity, and storage capacity, including general data centers, intelligent computing centers, supercomputing centers, etc.

[0058] The "supercomputing center" mentioned in the present invention refers to: a supercomputing data center, which is a data center based on a supercomputer or a large-scale computing cluster, which can provide large-scale computing, storage and network services and other functions, and is widely used in application scenarios such as aerospace, national defense, oil exploration, climate modeling and genome sequencing.

[0059] The "computing resources" mentioned in the present invention refer to: technologies and facilities with information computing, transmission, storage and application capabilities required for the development of a digital society, including but not limited to computing resources such as CPUs and GPUs, network resources such as switches and routers, storage resources such as storage arrays and distributed storage, security resources such as firewalls and intrusion detection systems, and supporting and guarantee resources such as wind, fire, water and electricity.

[0060] The "computing power operation task" mentioned in the present invention refers to: a specific workload or job executed on computing power resources that requires a certain amount of computing power support, usually involving complex data processing, numerical calculations, model training or simulation scenarios.

[0061] The "computing power operation task data" mentioned in the present invention refers to: a set of data used to describe and identify computing power resources. It is an identity card that records in detail the various attributes of this machine, this cluster, or this cloud instance, making it convenient to manage, schedule and use computing power resources.

[0062] Please refer to Figure 1 The present invention provides a method for idling computing tasks in an intelligent computing center, which is applied to the main thread and includes:

[0063] Step S1: Obtain the data recovery task of the computing power operation task to be completed;

[0064] In the present invention, the main thread is responsible for starting and managing the execution of the working thread, specifically including assigning tasks, scheduling the execution order of tasks and monitoring the status of tasks. In the actual production environment of multi-threaded parallel computing, the main thread can send empty tasks to the upper layer in a timely manner, and can also use existing logic to deal with no-load situations, without the need to create a system to handle it, thereby improving the availability of the entire system.

[0065] At the same time, the main thread also needs to coordinate data sharing and communication between different worker threads to ensure data consistency and correctness. The main thread is also responsible for catching and handling faults or exceptions that occur in worker threads to ensure system stability. By obtaining the number of computing power running subtasks and the number of worker threads specified by the user, the main thread can reasonably allocate resources to the worker threads, achieving more efficient resource utilization and flexible resource allocation.

[0066] Step S2: When the number of the computing power running task data recovery tasks to be completed is 0, confirm that the main thread is in a computing power running task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the computing power running task data recovery tasks to be completed;

[0067] In the present invention, in a system that processes heavy tasks, a method for processing empty tasks is also needed, that is, to process the case where the number of the acquired computing power running task data recovery tasks to be completed is 0. When the number of the acquired computing power running task data recovery tasks to be completed is 0, it is confirmed that the main thread is in the computing power running task no-load state, which means that the number of threads that need to be opened is 0, and the initialization thread slot is also 0, that is, no-load execution, and the task thread is not opened, thereby ensuring that tasks can be processed efficiently and reliably under high demand conditions, while optimizing resource allocation.

[0068] In the present invention, when the number of the computing power operation task data recovery tasks to be completed is not 0, that is, the computing power operation task data recovery task includes at least one computing power operation subtask, and the at least one computing power operation subtask constitutes a computing power operation task data recovery task queue; at least one working thread is created according to the computing power operation subtask, wherein the working thread is used to execute the computing power operation task data recovery task, and each working thread is used to execute at least one computing power operation subtask of the computing power operation task data recovery task. The working thread executes the specific computing tasks assigned to it, including but not limited to data recovery and data backup. The main thread manages and schedules the multiple computing power operation subtasks, and the multiple working threads execute tasks in parallel, which can significantly improve computing efficiency and shorten task completion time. During the execution of the task, the working thread can also capture and report faults or abnormal conditions so that the main thread can perform corresponding processing. After completing the task, the working thread usually returns the calculation results to the main thread or stores them in a shared data structure for subsequent processing or aggregation, thereby optimizing resource utilization and execution efficiency.

[0069] Specifically, the computing power running subtasks in the computing power running task data recovery task queue are arranged in reverse order, so that the working thread first obtains and executes the computing power running subtasks that are arranged at the back of the computing power running task data recovery task queue. Figure 2 By arranging the computing power running subtasks in the computing power running task data recovery task queue in reverse order, that is, arranging tasks 1, 2...task N+2 in the computing power running task data recovery task queue in reverse order, the working thread first obtains task N+2, and so on and finally obtains task 1, which can ensure that the system memory does not fluctuate, improve system performance, and enhance user satisfaction.

[0070] Step S3: according to the number of the to-be-completed computing power running task data recovery tasks being 0, confirming that the number of completed computing power running task data recovery tasks is greater than or equal to the to-be-completed computing power running task data recovery tasks, and confirming that all worker threads have exited;

[0071] In the present invention, since the number of computing power running task data recovery tasks to be completed is 0, the number of completed computing power running task data recovery tasks must be greater than or equal to the computing power running task data recovery tasks to be completed. Therefore, it can be confirmed that all working threads have exited, that is, the process of waiting for the execution of subsequent medium and heavy tasks can be exited, thereby avoiding unnecessary consumption of computing power resources and improving the robustness and stability of the intelligent computing center.

[0072] Step S4: Exit the main thread.

[0073] In the present invention, a data recovery task of computing power running tasks to be completed is obtained; when the number of the acquired data recovery tasks of computing power running tasks to be completed is 0, the main thread is confirmed to be in a computing power running task no-load state, and the number of created worker threads is set to 0, wherein the worker thread is used to execute the computing power running task data recovery task to be completed; based on the number of the computing power running task data recovery tasks to be completed being 0, it is confirmed that the number of completed computing power running task data recovery tasks is greater than or equal to the computing power running task data recovery task to be completed, and it is confirmed that all worker threads have exited; and the main thread is exited. A method for no-loading the computing power running tasks of an intelligent computing center is provided, which avoids unnecessary consumption of computing power resources, improves the robustness and stability of the intelligent computing center, and solves the problem of the lack of a method for no-loading the computing power running tasks of an intelligent computing center since the emergence of the intelligent computing center.

[0074] In the present invention, optionally, before step S1, the following steps are further included:

[0075] Step S0: Initialize the number of completed computing power running task data recovery tasks; and determine whether the task container sent by the user is valid, wherein the task container includes the computing power running task data recovery task; if the task container is invalid, directly exit the main thread; if the task container is valid, enter step S1.

[0076] In the present invention, by initializing the number of completed computing power running task data recovery tasks, it is convenient for subsequent processing when it is unloaded (for example: already_restore_region_datas=0), which can effectively manage and allocate computing resources to ensure that the system will not be overloaded. At the same time, it can also optimize the efficiency of resource utilization. By judging whether the task container sent by the user is valid, if it is invalid, the process of obtaining the task is skipped, potential errors or problems can be discovered in time, the burden on the system caused by invalid tasks can be avoided, the stability of the system can be improved, and the user experience can be improved.

[0077] In the present invention, optionally, step S2 includes:

[0078] Step S21: confirming that the main thread is in an idle state for computing task execution and setting the number of created worker threads to 0 are printed in the workbench and / or work log.

[0079] In the present invention, optionally, step S21 includes:

[0080] Step S211: Analyze and visualize the records in the workbench and / or work log in the form of charts or text.

[0081] In the present invention, the work execution process is tracked and recorded, and the main thread is confirmed to be in an idle state for computing power running tasks, and the execution status of setting the number of creation threads to 0, as well as the number of all failed creation work threads in other statistics, can be better handled in the system through failure records to ensure that the system can recover or take other measures in time when encountering problems, and if the creation of a work thread fails, the relevant resources can be released in time to avoid unnecessary resource occupation, which helps to improve the stability and performance of the system, and by printing statistical data on the workbench and / or work log and displaying statistical information in real time on the workbench, it can help operation and maintenance personnel and developers to immediately understand the system operation status and quickly discover potential problems, and through log records, help the team analyze the cause of the problem, facilitate subsequent troubleshooting and repair, and help to carry out strategic planning of resource allocation, performance optimization and system improvement, and ultimately improve the reliability of the system and user experience.

[0082] Specifically, the records in the workbench and / or work log can be analyzed in the form of charts (such as bar charts, line charts or pie charts) or text according to actual conditions, and visual output can be performed to more intuitively understand complex data and information, reduce analysis time, and improve system reliability and user experience.

[0083] Please refer to Figure 3 The specific workflow of the main thread execution computing power running task no-load method is as follows:

[0084] First, the main thread is constructed and the number of completed computing power running task data recovery tasks is initialized, that is, the number of processed tasks is initialized to 0;

[0085] Then, the computing power running task data recovery task is initialized, that is, whether the task container sent by the user is valid, wherein the task container includes the computing power running task data recovery task; if the task container is invalid, the task acquisition process is skipped and the main thread is directly exited; if the task container is valid, whether there is a task in the task container is determined; if there is a task, the task information is printed; if the number of tasks is greater than 1, the tasks in the task container are flipped; if there is no task, no load is executed;

[0086] Finally, during the running process, when the number of the computing power running task data recovery tasks to be completed is 0, it is confirmed that the main thread is in the computing power running task no-load state, and the number of created working threads is set to 0, wherein the working thread is used to execute the computing power running task data recovery tasks to be completed; according to the number of the computing power running task data recovery tasks to be completed being 0, it is confirmed that the number of completed computing power running task data recovery tasks is greater than or equal to the computing power running task data recovery tasks to be completed, and it is confirmed that all working threads have exited; and the main thread exits.

[0087] Please refer to Figure 4 , the present invention provides a main thread, including:

[0088] The acquisition module 41 is used to obtain the data recovery task of the computing power operation task to be completed;

[0089] The first processing module 42 is configured to, when the number of the to-be-completed computing power operation task data recovery tasks is 0, confirm that the main thread is in a computing power operation task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the to-be-completed computing power operation task data recovery tasks;

[0090] The second processing module 43 is configured to confirm that the number of completed computing power operation task data recovery tasks is greater than or equal to the computing power operation task data recovery tasks to be completed, and confirm that all working threads have exited, based on the number of the computing power operation task data recovery tasks to be completed being 0.

[0091] The exit module 44 is used to exit the main thread.

[0092] The present invention may optionally further include:

[0093] An initialization module is used to initialize the number of completed computing power operation task data recovery tasks; and to determine whether the task container sent by the user is valid, wherein the task container includes the computing power operation task data recovery task; if the task container is invalid, the main thread is directly exited; if the task container is valid, step S1 is entered.

[0094] In the present invention, optionally, the first processing module includes:

[0095] The first processing submodule is used to print the execution status of confirming that the main thread is in an idle state for computing power running tasks and setting the number of created working threads to 0 in the workbench and / or work log.

[0096] In the present invention, optionally, the first processing module includes:

[0097] The second processing submodule is used to analyze and visualize the records in the workbench and / or work log in the form of charts or text.

[0098] The main thread provided by the present invention can realize Figure 1 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0099] The present invention provides an electronic device 50, see Figure 5 As shown, Figure 5 This is a principle block diagram of an electronic device 50 of the present invention, including a processor 51, a memory 52, and a program or instruction stored in the memory 52 and executable on the processor 51. When the program or instruction is executed by the processor, the steps in the method for idling computing power operation tasks of any intelligent computing center of the present invention are implemented.

[0100] The present invention provides a readable storage medium, which stores programs or instructions. When the programs or instructions are executed by a processor, the various processes of the embodiments of the computing power running task idling method of the intelligent computing center such as any of the above-mentioned items are implemented, and the same technical effects can be achieved. To avoid repetition, they will not be described here.

[0101] The present application also provides a computer program product including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of the method embodiment shown can achieve the same technical effect, and to avoid repetition, they will not be described here.

[0102] Computer-readable media includes both permanent and non-permanent, removable and non-removable media, and can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0103] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, and storage of user personal information involved in the technical solutions disclosed herein comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken with respect to user personal information to prevent unauthorized access to user personal information data and maintain the security of user personal information and network security.

[0104] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0105] The above serial numbers of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0106] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a service classification device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0107] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for idling computing tasks in an intelligent computing center, characterized in that: Applied to the main thread, including: Step S1: Obtain the data recovery task of the computing power operation task to be completed; Step S2: When the number of the computing power running task data recovery tasks to be completed is 0, confirm that the main thread is in the computing power running task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the computing power running task data recovery tasks to be completed; Step S3: according to the number of the to-be-completed computing power running task data recovery tasks being 0, confirming that the number of completed computing power running task data recovery tasks is greater than or equal to the to-be-completed computing power running task data recovery tasks, and confirming that all worker threads have exited; Step S4: Exit the main thread.

2. The method for idling computing tasks in an intelligent computing center according to claim 1, characterized in that: Before step S1, the method further includes: Step S0: Initialize the number of completed computing power operation task data recovery tasks; and determine whether the task container sent by the user is valid, wherein the task container includes the computing power operation task data recovery task; if the task container is invalid, enter the step S1; if the task container is valid, enter the step S1.

3. The method for idling computing tasks in an intelligent computing center according to claim 1, characterized in that: The step S2 comprises: Step S21: confirming that the main thread is in an idle state for computing task execution and setting the number of created worker threads to 0 are printed in the workbench and / or work log.

4. The method for idling computing tasks in an intelligent computing center according to claim 3, characterized in that: The step S21 includes: Step S211: Analyze and visualize the records in the workbench and / or work log in the form of charts or text.

5. A main thread, characterized in that, include: The acquisition module is used to obtain the data recovery tasks of the computing power running tasks to be completed; A first processing module is configured to, when the number of the to-be-completed computing power operation task data recovery tasks obtained is 0, confirm that the main thread is in a computing power operation task idle state, and set the number of created worker threads to 0, wherein the worker threads are used to execute the to-be-completed computing power operation task data recovery tasks; A second processing module is used to confirm that the number of completed computing power running task data recovery tasks is greater than or equal to the computing power running task data recovery tasks to be completed, and confirm that all working threads have exited; The exit module is used to exit the main thread.

6. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein when the program or instruction is executed by the processor, the steps in the method for idling computing power operation tasks of an intelligent computing center as described in any one of claims 1 to 4 are implemented.

7. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps in the computing power operation task idling method of the intelligent computing center as described in any one of claims 1 to 4 are implemented.

8. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps in the method for idling computing tasks of an intelligent computing center as described in any one of claims 1 to 4.

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