Low-delay network detection method and device for computing power resource data of intelligent computing center

Abstract

The invention provides a low-delay network detection method and device for computing power resource data of an intelligent computing center. The method comprises the following steps: S1, acquiring a network performance detection instruction for detecting a target client and / or a target server; s2, calling a network performance detection tool according to the network performance detection instruction to obtain real-time bandwidth and real-time delay of the target client and / or the target server; and S3, comparing the real-time bandwidth with a preset bandwidth threshold value, and comparing the real-time delay with a preset delay threshold value to obtain a target network detection result. According to the invention, the operation efficiency of the intelligent computing center is improved through the low-delay network detection of the data of the computing power resources of the intelligent computing center.

Description

Technical Field

[0001] The present invention relates to the technical fields of intelligent computing centers, intelligent computing centers, and computing power infrastructure technologies, and in particular, to a method and device for low-latency network detection of computing power resource data 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 as the times require.

[0003] An "intelligent computing center" refers to a facility that uses large-scale heterogeneous computing power resources, including general computing power and intelligent computing power, and mainly provides the required computing power, data, and algorithms for artificial intelligence applications (such as scenarios of artificial intelligence deep learning model development, model training, and model inference, etc.). The intelligent computing center covers facilities, hardware, and software, and can provide full-stack capabilities from underlying computing power to top-level application enabling.

[0004] The "intelligent computing center" includes but is not limited to the "intelligent computing center".

[0005] An "intelligent computing center", that is, an artificial intelligence computing center, is a type of computing power infrastructure that is based on artificial intelligence theory, adopts an 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 centers" and "intelligent computing centers", and is the ability of computer devices or computing / data centers to process information. It is the ability of computer hardware and software to cooperate to jointly execute a certain computing requirement. It is the computing ability to achieve the output of the target result by processing information data. It is a new type of productive force that integrates information computing power, network carrying capacity, and data storage capacity, and mainly provides services to society through computing power infrastructure.

[0007] Currently, during the data transmission process of the computing power resources in an intelligent computing center, there is a lack of low-latency network detection for the computing power resource data of the intelligent computing center. In actual applications, if low-latency network detection is not performed, it will lead to increased network latency, degraded performance, and slow fault recovery, affecting the operation efficiency of the intelligent computing center. Summary of the Invention

[0008] The present invention provides a method and device for low-latency network detection of computing power resource data in an intelligent computing center to solve the problem of the lack of low-latency network detection for the computing power resource data of the intelligent computing center during the use of existing computing power resources.

[0009] To solve the above technical problems, the present invention is implemented as follows:

[0010] In a first aspect, the present invention provides a method for low-latency network detection of computing power resource data in an intelligent computing center, including:

[0011] Step S1: Obtain a network performance detection instruction for detecting a target client and / or a target server;

[0012] Step S2: Call a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server;

[0013] Step S3: Compare the real-time bandwidth with a preset bandwidth threshold, and compare the real-time delay with a preset delay threshold to obtain a target network detection result.

[0014] Optionally, the network performance detection tool includes: ib_send_bw or ib_write_bw.

[0015] Optionally, step S1 includes:

[0016] Obtain a network performance detection instruction for periodically detecting the target client and / or the target server according to a preset monitoring period.

[0017] Optionally, step S3 includes:

[0018] When any judgment condition is not met, the target network detection result is that the target network does not meet the requirements;

[0019] When all judgment conditions are met, the target network detection result is that the target network meets the requirements;

[0020] The judgment conditions include: the real-time bandwidth is not less than the preset bandwidth threshold;

[0021] The real-time delay is not greater than the preset delay threshold.

[0022] Optionally, the preset bandwidth threshold is 390 ± 5 Gbps;

[0023] The preset delay threshold is 10 ± 2 us.

[0024] Optionally, after step S3, it further includes:

[0025] Step S4: Analyze the target client and / or the target server according to the target network detection result to obtain an analysis result; and perform network configuration adjustment on the target client and / or the target server according to the analysis result.

[0026] Second aspect, the present invention provides a low-latency network detection device for computing power resource data of an intelligent computing center, including:

[0027] An acquisition module, configured to acquire a network performance detection instruction for detecting a target client and / or a target server;

[0028] A detection module, configured to call a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server;

[0029] A comparison module, configured to compare the real-time bandwidth with a preset bandwidth threshold, and compare the real-time delay with a preset delay threshold to obtain a target network detection result.

[0030] Optionally, the network performance detection tool includes: ib_send_bw or ib_write_bw.

[0031] Optionally, a monitoring module, configured to acquire a network performance detection instruction for periodically detecting the target client and / or the target server according to a preset monitoring period.

[0032] Optionally, the comparison module includes:

[0033] A first comparison sub-module, configured to when any judgment condition is not satisfied, the target network detection result is that the target network does not meet the requirements;

[0034] A first and second comparison sub-module, configured to when all judgment conditions are satisfied, the target network detection result is that the target network meets the requirements;

[0035] The judgment conditions include: the real-time bandwidth is not less than the preset bandwidth threshold;

[0036] The real-time delay is not greater than the preset delay threshold.

[0037] Optionally, the preset bandwidth threshold is 390 ± 5 Gbps; the preset delay threshold is 10 ± 2 us.

[0038] Optionally, a processing module, configured to analyze the target client and / or the target server according to the target network detection result to obtain an analysis result; and perform network configuration adjustment on the target client and / or the target server according to the analysis result.

[0039] In a third aspect, the present invention provides an electronic device, including a processor, a memory, and a program or instructions stored on the memory and executable on the processor. When the program or instructions are executed by the processor, the steps in the low-latency network detection method for computing power resource data of the intelligent computing center described in any one of the first aspects are implemented.

[0040] In a fourth aspect, the present invention provides a readable storage medium with a program or instructions stored thereon. When the program or instructions are executed by a processor, the steps in the low-latency network detection method for computing power resource data of the intelligent computing center described in any one of the first aspects are implemented.

[0041] In a fifth aspect, the present invention provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the steps in the low-latency network detection method for computing power resource data of the intelligent computing center described in any one of the first aspects are implemented.

[0042] In the present invention, a network performance detection instruction for detecting a target client and / or a target server is obtained; a network performance detection tool is called according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server; the real-time bandwidth is compared with a preset bandwidth threshold, and the real-time delay is compared with a preset delay threshold to obtain a target network detection result. By performing low-latency network detection on the computing power resource data of the intelligent computing center, the operation efficiency of the intelligent computing center is improved, and the problem of lacking low-latency network detection for the computing power resource data of the intelligent computing center in the existing use process of computing power resources is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0044] Figure 1 is a flowchart of a low-latency network detection method for computing power resource data of an intelligent computing center provided by the present invention;

[0045] Figure 2 is a schematic diagram of bandwidth detection of a low-latency network detection method for computing power resource data of an intelligent computing center provided by the present invention;

[0046] Figure 3 is a schematic diagram of delay detection of a low-latency network detection method for computing power resource data of an intelligent computing center provided by the present invention;

[0047] Figure 4 It is a schematic structural diagram of a low-latency network detection device for computing power resource data of an intelligent computing center provided by the present invention;

[0048] Figure 5 It is a schematic structural diagram of an electronic device provided by the present invention. Specific embodiments

[0049] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0050] First, the technical terms related to the present invention will be briefly described below.

[0051] The "computing power" described in the present invention refers to: the ability of a computer device or a computing / data center to process information, the ability of computer hardware and software to cooperate to jointly execute a certain computing requirement, the computing ability to output a target result through processing information data, a new type of productive force integrating information computing power, network carrying capacity, and data storage capacity, and mainly providing services to society through computing power infrastructure.

[0052] The "computational power" (CP) described in the present invention refers to: the ability of a data center server to process data and output results, a comprehensive index for measuring the computing ability of a data center, including general computing ability, supercomputing ability, and intelligent computing ability. The commonly used measurement unit is the number of floating-point operations per second (FLOPS, 1EFLOPS = 10^18 FLOPS), and the larger the value, the stronger the comprehensive computing ability. It is estimated that 1EFLOPS is approximately the computing power output of 5 Tianhe 2A or 500,000 mainstream server CPUs or 2 million mainstream laptops. The calculation formula is: CP = CP 通用 +CP 智能 +CP 超级 .

[0053] The "carrying capacity" (Network Power, NP) described in the present invention refers to: the performance of the data transmission ability of computing power facilities, a comprehensive ability including network architecture, network bandwidth, transmission delay, intelligent management and scheduling, etc., involving network transmission inside and between data centers, and a comprehensive index for measuring network transmission scheduling ability.

[0054] The "Storage Power (SP)" described in the present invention refers to the comprehensive ability of a data center in four aspects: data storage capacity, performance, security and reliability, and green and low-carbon. It is a comprehensive indicator for measuring the data storage capacity of a data center, including external storage devices such as storage arrays and built-in storage devices of servers. The commonly used measurement unit for storage capacity is exabyte (EB, 1EB = 2^60 bytes), the commonly used measurement unit for performance is the number of read and write operations per second per unit capacity (IOPS / TB, Input / Output Operations Per Second / TB), and the disaster recovery ratio is an important manifestation of security and reliability.

[0055] The "computing power infrastructure" described in the present invention refers to a new type of information infrastructure that integrates information computing power, network carrying capacity, and data storage power, and can realize the centralized computing, storage, transmission, and application of information.

[0056] The "new type of information infrastructure" described in the present invention mainly includes network infrastructures such as 5G networks, fiber broadband networks, backbone networks, international communication networks, and satellite Internet, computing power infrastructures such as data centers, general computing power centers, intelligent computing centers, and supercomputing centers, and new technology facilities such as artificial intelligence, blockchain, and quantum computing.

[0057] The "computing power" described in the present invention includes: general computing power, intelligent computing power, and super computing power.

[0058] The "general computing power" described 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.

[0059] The "intelligent computing power" described in the present invention refers to a computing platform that is scaled for various artificial intelligence innovation applications based on dedicated chips such as GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array), and ASIC (Application Specific Integrated Circuit), such as natural language processing and machine vision.

[0060] The "super computing power" described in the present invention mainly 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 processes extremely complex or data-intensive problems through a dedicated operating system. It is mainly used for computing in cutting-edge scientific fields, such as planetary simulation, drug molecule design, and gene analysis.

[0061] The "Intelligent Computing Center" described in the present invention refers to a facility that mainly provides the required computing power, data, and algorithms for artificial intelligence applications (such as scenarios like artificial intelligence deep learning model development, model training, and model inference) by using large-scale heterogeneous computing power resources, including general computing power (CPU) and intelligent computing power (GPU, FPGA, ASIC, etc.). The intelligent computing center covers facilities, hardware, and software, and can provide full-stack capabilities from underlying computing power to top-level application enabling.

[0062] The "Intelligent Computing Center" described in the present invention includes, but is not limited to, the "Intelligent Computing Center".

[0063] The "Intelligent Computing Center" described in the present invention, namely the artificial intelligence computing center, is a type of computing power infrastructure that provides computing power services, data services, and algorithm services required for artificial intelligence applications based on artificial intelligence theory and adopting an artificial intelligence computing architecture.

[0064] The "Computing Power Center" described in the present invention refers to a facility mainly composed of infrastructure such as wind, fire, water, and electricity and IT software and hardware devices, and having computing power, carrying capacity, and storage capacity, including general data centers, intelligent computing centers, supercomputing centers, etc.

[0065] The "Supercomputing Center" described in the present invention, namely the supercomputing data center, is a data center based on supercomputers or large-scale computing clusters, capable of providing functions such as large-scale computing, storage, and network services, and is widely used in application scenarios such as aerospace, national defense, oil exploration, climate modeling, and genome sequencing.

[0066] The "Computing Power Resources" described in the present invention refers to technologies and facilities required for the development of the digital society and having information computing, transmission, storage, and application capabilities, including but not limited to computing resources such as CPU and GPU, 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 support and guarantee resources such as wind, fire, water, and electricity.

[0067] The "Low-Latency Network" described in the present invention refers to networks such as Infinite Bandwidth (InfiniBand, IB) and Remote Direct Memory Access over Converged Ethernet (RoCE), which can achieve ultra-low-latency data communication.

[0068] Please refer to Figure 1 , the present invention provides a method for detecting low-latency network of computing power resources of an intelligent computing center, including:

[0069] Step S1: Obtain a network performance detection instruction for detecting a target client and / or a target server;

[0070] In the present invention, a network performance detection instruction for detecting the target client and / or the target server can be directly obtained. By detecting the network performance, network problems can be identified and located, so as to quickly take measures to solve the faults, optimize the network configuration and resource allocation, and improve the overall network performance.

[0071] In the present invention, optionally, step S1 includes:

[0072] Obtaining a network performance detection instruction for periodically detecting the target client and / or the target server according to a preset monitoring period.

[0073] In the present invention, a network performance detection instruction can also be obtained periodically. By monitoring the target client and / or the target server, network performance detection is performed regularly to monitor the service quality and improve user satisfaction. And through the long-term monitoring of the network performance, capacity planning can be better carried out, future traffic demands can be predicted, network resources can be reasonably allocated, the user experience can be improved by optimizing the network performance, the loading time can be reduced, and the response speed of the application program can be increased.

[0074] Step S2: Invoking a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server;

[0075] In the present invention, optionally, the network performance detection tool includes: ib_send_bw or ib_write_bw.

[0076] In the present invention, the network performance can be detected by but not limited to using ib_send_bw and ib_write_bw. Please refer to Figure 2 and Figure 3 In order to obtain the real-time bandwidth and real-time delay of the target client and / or the target server, through the network performance detection of the target client and / or the target server, the best configuration is found to optimize the network performance and ensure efficient network operation.

[0077] Step S3: Comparing the real-time bandwidth with a preset bandwidth threshold, and comparing the real-time delay with a preset delay threshold to obtain a target network detection result.

[0078] In the present invention, the real-time bandwidth is compared with a preset bandwidth threshold, and the real-time delay is compared with a preset delay threshold to monitor the network performance in real time and evaluate whether the network reaches the expected service level, so as to timely detect the trend of performance degradation and ensure that the network operates within an acceptable range. When the real-time bandwidth or the real-time delay fails to meet the preset threshold, potential network problems such as network congestion, device failure or configuration error can be quickly identified. Through the target network detection result, network administrators or automated devices can locate and solve problems faster, reduce the fault recovery time, improve the overall network performance, and ensure the efficient utilization of network resources.

[0079] In the present invention, optionally, the step S3 includes:

[0080] When any one of the judgment conditions is not met, the target network detection result is that the target network does not meet the requirements;

[0081] When all the judgment conditions are met, the target network detection result is that the target network meets the requirements;

[0082] The judgment conditions include: the real-time bandwidth is not less than the preset bandwidth threshold;

[0083] The real-time delay is not greater than the preset delay threshold.

[0084] In the present invention, optionally, the preset bandwidth threshold is 390 ± 5 Gbps;

[0085] The preset delay threshold is 10 ± 2 us.

[0086] In the present invention, it is set that when both the real-time bandwidth and the real-time delay meet the requirements, the target network detection result is that the target network meets the requirements. Considering both bandwidth and delay can more comprehensively evaluate the network performance, ensure that there will be no bottlenecks or delays during data transmission, thereby improving the user experience. And by using a dual standard to judge the network quality, misjudgment caused by fluctuations in a single index can be reduced, and the reliability of the network detection result can be improved. When both the bandwidth and the delay meet the requirements, network resources can be utilized more effectively, avoiding resource waste caused by network quality problems and enhancing user satisfaction.

[0087] In the present invention, a network performance detection instruction for detecting a target client and / or a target server is obtained; a network performance detection tool is called according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server; the real-time bandwidth is compared with a preset bandwidth threshold, and the real-time delay is compared with a preset delay threshold to obtain a target network detection result. By performing data low-latency network detection on the computing power resources of the intelligent computing center, the operation efficiency of the intelligent computing center is improved, and the problem that there is a lack of data low-latency network detection for the computing power resources of the intelligent computing center in the existing process of using computing power resources is solved.

[0088] In the present invention, optionally, after the step S3, the following is further included:

[0089] Step S4: Analyze the target client and / or the target server according to the target network detection result to obtain an analysis result; and perform network configuration adjustment on the target client and / or the target server according to the analysis result.

[0090] In the present invention, through real-time monitoring and data comparison, the target client and / or the target server are analyzed, more scientific decisions are made based on the analysis results, network policies are optimized, and a visual report can be provided. By analyzing the collected target network detection results, potential performance bottlenecks are identified, so as to evaluate whether the configurations of the target client and the target server match the network requirements, and a corresponding network configuration adjustment plan is formulated. For example: increasing bandwidth limits, optimizing routing settings, adjusting service quality policies to prioritize important traffic, and performing load balancing to disperse traffic loads; after performing network configuration adjustment on the target client and / or the target server according to the analysis result, continuously monitor the network performance to ensure that the adjustment measures are effective. Through targeted adjustment, the network performance is optimized, latency and packet loss are reduced, the data transmission rate is increased, the effective utilization of bandwidth and computing resources is ensured, resource waste is avoided, and network problems are quickly identified and solved through real-time monitoring and analysis, thereby reducing the failure time and improving the availability of the system.

[0091] Please refer to Figure 4 , the present invention provides a data low-latency network detection device for the computing power resources of an intelligent computing center, including:

[0092] An acquisition module 41, configured to acquire a network performance detection instruction for detecting a target client and / or a target server;

[0093] A detection module 42, configured to call a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server;

[0094] A comparison module 43, configured to compare the real-time bandwidth with a preset bandwidth threshold, and compare the real-time delay with a preset delay threshold, to obtain a target network detection result.

[0095] In the present invention, optionally, the network performance detection tool includes: ib_send_bw or ib_write_bw.

[0096] In the present invention, optionally, a monitoring module is configured to obtain a network performance detection instruction for periodically detecting the target client and / or the target server according to a preset monitoring period.

[0097] In the present invention, optionally, the comparison module includes:

[0098] A first comparison sub-module, configured to when any one of the judgment conditions is not satisfied, the target network detection result is that the target network does not meet the requirements;

[0099] A first and second comparison sub-module, configured to when all the judgment conditions are satisfied, the target network detection result is that the target network meets the requirements;

[0100] The judgment conditions include: the real-time bandwidth is not less than the preset bandwidth threshold;

[0101] The real-time delay is not greater than the preset delay threshold.

[0102] In the present invention, optionally, the preset bandwidth threshold is 390±5 Gbps; the preset delay threshold is 10±2 us.

[0103] In the present invention, optionally, a processing module is configured to analyze the target client and / or the target server according to the target network detection result to obtain an analysis result; and perform network configuration adjustment on the target client and / or the target server according to the analysis result.

[0104] The low-latency network detection device for computing power resource data of the intelligent computing center provided by the present invention can implement Figure 1 each process implemented by the method embodiment, and achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0105] The present invention provides an electronic device 50, as shown in Figure 5 shown, Figure 5 is a schematic block diagram of the 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 any one of the low-latency network detection methods for computing power resource data of the intelligent computing center of the present invention are implemented.

[0106] The present invention provides a readable storage medium, on which a program or instructions are stored. When the program or instructions are executed by a processor, the various processes of the embodiment of the method for low-latency network detection of computing power resource data of the intelligent computing center as described in any of the above are implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0107] The embodiment of the present application further provides a computer program product, including computer instructions, which when executed by a processor implement the various processes of the method embodiment as described above Figure 1 and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0108] Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The 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 memory (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 cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media do not include transitory media such as modulated data signals and carrier waves.

[0109] It should be noted that in the technical solution of the present disclosure, in terms of the collection, gathering, updating, analysis, processing, use, transmission, storage, etc. of the user's personal information, it complies with the provisions of relevant laws and regulations, is used for legal purposes, and does not violate public order and good customs. Necessary measures are taken for the user's personal information to prevent illegal access to the user's personal information data and to maintain the security of the user's personal information and network security.

[0110] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or device including that element.

[0111] The above serial numbers of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0112] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to enable a service classification device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0113] The above is only the preferred embodiment of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A low-latency network detection method for computing resource data in an intelligent computing center, characterized in that: include: Step S1: obtaining a network performance detection instruction for detecting a target client and / or a target server; Step S2: calling a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server; Step S3: Compare the real-time bandwidth with a preset bandwidth threshold, and compare the real-time delay with a preset delay threshold to obtain a target network detection result.

2. The low-latency network detection method for computing resource data of an intelligent computing center according to claim 1 is characterized in that: The network performance detection tool includes: ib_send_bw or ib_write_bw.

3. The low-latency network detection method for computing resource data of an intelligent computing center according to claim 1 is characterized in that: The step S1 comprises: A network performance detection instruction for periodically detecting the target client and / or the target server is obtained according to a preset monitoring period.

4. The method for low-latency network detection of computing resource data of an intelligent computing center according to claim 1 is characterized in that: The step S3 comprises: When any judgment condition is not met, the target network detection result is that the target network does not meet the requirements; When all the judgment conditions are met, the target network detection result is that the target network meets the requirements; The judgment condition includes: the real-time bandwidth is not less than the preset bandwidth threshold; The real-time delay is no greater than the preset delay threshold.

5. The low-latency network detection method for computing resource data of an intelligent computing center according to claim 1 is characterized in that: The preset bandwidth threshold is 390±5 Gbps; The preset delay threshold is 10±2us.

6. The method for low-latency network detection of computing resource data of an intelligent computing center according to claim 1, characterized in that: After step S3, the method further includes: Step S4: analyzing the target client and / or the target server according to the target network detection result to obtain an analysis result; and adjusting the network configuration of the target client and / or the target server according to the analysis result.

7. A low-latency network detection device for computing resource data in an intelligent computing center, characterized in that: include: An acquisition module is used to acquire a network performance detection instruction for detecting a target client and / or a target server; A detection module, used to call a network performance detection tool according to the network performance detection instruction to obtain the real-time bandwidth and real-time delay of the target client and / or the target server; The comparison module is used to compare the real-time bandwidth with a preset bandwidth threshold, and to compare the real-time delay with a preset delay threshold, so as to obtain a target network detection result.

8. 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. When the program or instruction is executed by the processor, the steps in the low-latency network detection method for computing resource data of an intelligent computing center as described in any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized in that: The readable storage medium stores programs or instructions, which, when executed by a processor, implement the steps in the low-latency network detection method for computing resource data of an intelligent computing center as described in any one of claims 1 to 6.

10. A computer program product, characterized in that It includes computer instructions, which, when executed by a processor, implement the steps in the low-latency network detection method for computing resource data of an intelligent computing center as described in any one of claims 1 to 6.

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