Method and device for manual capacity expansion and auditing of computing power of intelligent computing center cloud platform

Abstract

The invention provides a computing power manual capacity expansion and auditing method and device for an intelligent computing center cloud platform, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructures, and the method comprises the steps: S1, receiving a capacity expansion instruction sent by a user through an interaction end, the capacity expansion instruction comprises a computing power parameter adjusted by a user, a storage parameter adjusted by the user and a network bandwidth parameter adjusted by the user; s2, according to the computing power parameter, the storage parameter and the network bandwidth parameter, checking whether the capacity expansion instruction meets a preset capacity expansion rule or not, and obtaining a checking result; and S3, if the auditing result indicates that the capacity expansion instruction meets the capacity expansion rule and the pre-estimated computing power cost after capacity expansion does not exceed a preset budget threshold, carrying out capacity expansion on the computing power of the user according to the capacity expansion instruction, so that the capacity expansion of the computing power of the individual user according to needs is realized, the flexibility of computing power distribution is improved, and the user experience is improved. And the utilization efficiency of computing power can be improved.

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 particularly relates to a method and device for manual expansion and auditing of computing power in an intelligent computing center cloud platform. 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 provides the required computing power, data, and algorithms mainly 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 and intelligent computing power. 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 provides computing power services, data services, and algorithm services required for artificial intelligence applications based on artificial intelligence theory and using an artificial intelligence computing architecture.

[0006] "Computing power" is the core of "intelligent computing centers" and "intelligent computing centers", which is the ability of computer devices or computing / data centers to process information, the ability of computer hardware and software to cooperate to jointly execute a certain computing requirement, the computing ability to achieve the output of target results by processing information data, a new type of productive force integrating information computing power, network carrying capacity, and data storage capacity, and mainly provides services to society through computing power infrastructure.

[0007] Since the emergence of intelligent computing centers, the problem that individual users cannot perform computing power expansion operations has been a problem to be solved. Individual users cannot expand computing power on demand and can only rely on service provider preset packages, which easily leads to computing power waste or performance bottlenecks and causes rigid computing power allocation. Summary of the Invention

[0008] The present invention provides a method and device for manual expansion and auditing of computing power in an intelligent computing center cloud platform to solve the problem that individual users cannot expand computing power on demand and can only rely on service provider preset packages, which easily leads to computing power waste or performance bottlenecks and causes rigid computing power allocation.

[0009] To solve the above technical problems, the present invention is implemented as follows: In a first aspect, the present invention provides a method for manual expansion and auditing of computing power in an intelligent computing center cloud platform, including: Step S1: Receive the expansion instruction sent by the user through the interaction terminal. The expansion instruction includes: the computing power parameters adjusted by the user, the storage parameters adjusted by the user, and the network bandwidth parameters adjusted by the user. Step S2: According to the computing power parameters, the storage parameters, and the network bandwidth parameters, verify whether the expansion instruction meets the preset expansion rules to obtain a verification result. Step S3: If the verification result indicates that the expansion instruction meets the expansion rules and the pre-estimated computing power cost after expansion does not exceed the preset budget threshold, expand the user's computing power according to the expansion instruction.

[0010] Optionally, step S2 includes: Step S21: According to the computing power parameters, the storage parameters, and the network bandwidth parameters, determine whether the expansion instruction is an abnormal instruction that exceeds the preset over-allocation threshold. Step S22: If the expansion instruction is not the abnormal instruction, input the user's credit score, the user's historical computing power usage, the user's account balance information, the computing power parameters, the storage parameters, and the network bandwidth parameters into the pre-trained verification model to obtain the verification result. Step S23: If the expansion instruction is the abnormal instruction, generate an artificial verification task and send the artificial verification task to the administrator terminal associated with the administrator, and use the artificial verification result obtained after the administrator terminal completes the artificial verification task as the verification result.

[0011] Optionally, after step S2, it includes: Step S3': If the verification result indicates that the expansion instruction does not meet the expansion rules, terminate the expansion, generate a first error message indicating that the expansion instruction does not meet the expansion rules, and send the first error message to the interaction terminal.

[0012] Optionally, after step S2, it includes: Step S3'': In the case where the verification result indicates that the expansion instruction meets the expansion rules, if the pre-estimated computing power cost after expansion exceeds the budget threshold, terminate the expansion, generate a second error message indicating that it exceeds the budget threshold, and send the second error message to the interaction terminal.

[0013] Optionally, each user has an independent resource space divided by containerization technology; Step S3 includes: Step S31: Expand within the resource space corresponding to the user according to the expansion instruction.

[0014] Optionally, step S3 includes: Step S32: Dynamically expand the network bandwidth through software-defined networking.

[0015] In a second aspect, the present invention provides a device for manually expanding and auditing the computing power of an intelligent computing center cloud platform, including: A receiving module, configured to receive an expansion instruction sent by a user through an interaction terminal, where the expansion instruction includes: computing power parameters adjusted by the user, storage parameters adjusted by the user, and network bandwidth parameters adjusted by the user; An auditing module, configured to audit whether the expansion instruction meets a preset expansion rule according to the computing power parameters, the storage parameters, and the network bandwidth parameters, and obtain an audit result; An execution module, configured to expand the user's computing power according to the expansion instruction if the audit result indicates that the expansion instruction meets the expansion rule and the pre-estimated computing power cost after expansion does not exceed a preset budget threshold.

[0016] In a third aspect, the present invention provides an electronic device, including a processor, a memory, and a program or instruction stored on the memory and executable on the processor, where when the program or instruction is executed by the processor, the steps in the method for manually expanding and auditing the computing power of the intelligent computing center cloud platform according to any one of the first aspects are implemented.

[0017] In a fourth aspect, the present invention provides a readable storage medium, where a program or instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps in the method for manually expanding and auditing the computing power of the intelligent computing center cloud platform according to any one of the first aspects are implemented.

[0018] In a fifth aspect, the present invention provides a computer program product, including computer instructions, where when the computer instructions are executed by a processor, the steps in the method for manually expanding and auditing the computing power of the intelligent computing center cloud platform according to any one of the first aspects are implemented.

[0019] In the present invention, through Step S1: receiving an expansion instruction sent by a user through an interaction terminal, where the expansion instruction includes: computing power parameters adjusted by the user, storage parameters adjusted by the user, and network bandwidth parameters adjusted by the user; Step S2: auditing whether the expansion instruction meets a preset expansion rule according to the computing power parameters, the storage parameters, and the network bandwidth parameters, and obtaining an audit result; Step S3: expanding the user's computing power according to the expansion instruction if the audit result indicates that the expansion instruction meets the expansion rule and the pre-estimated computing power cost after expansion does not exceed a preset budget threshold, the present invention realizes on-demand expansion of computing power for individual users, improves the flexibility of computing power allocation, and is conducive to improving the utilization efficiency of computing power. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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: Figure 1 is a schematic flow chart of the method for manually expanding and auditing the computing power of the cloud platform of the intelligent computing center of the present invention; Figure 2 is a schematic block diagram of the principle of the device for manually expanding and auditing the computing power of the cloud platform of the intelligent computing center of the present invention; Figure 3 is a schematic block diagram of the principle of the electronic device of the present invention. Specific embodiments

[0021] Next, the technical solutions in the present invention will be clearly and completely described in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts fall within the scope of protection of the present invention.

[0022] The terms "first", "second", etc. in the present invention are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so that the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are usually of the same category, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "or" in the present invention means at least one of the connected objects. For example, "A or B" covers three scenarios, namely, Scenario 1: including A and not including B; Scenario 2: including B and not including A; Scenario 3: including both A and B. The character " / " generally indicates that the related objects before and after are in an "or" relationship.

[0023] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0024] Next, a brief description will be given first to the technical terms involved in the present invention.

[0025] 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 process information data and output a target result, 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.

[0026] The "Computational Power" (CP) described in the present invention refers to: the ability of a data center server to process data and output results, which is a comprehensive indicator for measuring the computing power of a data center and includes general computing power, supercomputing power, and intelligent computing power. The commonly used measurement unit is the number of floating-point operations per second (FLOPS, 1 EFLOPS = 10^18 FLOPS), and the larger the value, the stronger the comprehensive computing power. It is estimated that 1 EFLOPS 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 。

[0027] The "Network Power" (NP) described in the present invention refers to: the performance of the data transmission capacity of computing power facilities, which is a comprehensive ability including network architecture, network bandwidth, transmission delay, intelligent management and scheduling, etc., and involves network transmission within and between data centers, and is a comprehensive indicator for measuring network transmission scheduling ability.

[0028] 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, which is a comprehensive indicator for measuring the data storage ability of a data center and includes external storage devices such as storage arrays and server-internal storage devices. The commonly used measurement unit for storage capacity is exabyte (EB, 1 EB = 2^60 bytes), and 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). The disaster recovery ratio is an important manifestation of security and reliability.

[0029] The "computing power infrastructure" described in the present invention refers to: a new type of information infrastructure that integrates information computing power, network carrying power, and data storage power, and can realize the centralized computing, storage, transmission, and application of information.

[0030] 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.

[0031] The "computing power" described in the present invention includes: general computing power, intelligent computing power, and supercomputing power.

[0032] 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.

[0033] The "intelligent computing power" described in the present invention refers to a computing platform that is scaled and deployed 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, machine vision, and so on.

[0034] 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, gene analysis, etc.

[0035] The "intelligent computing center" described in the present invention refers to a facility that 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.

[0036] The "intelligent computing center cloud platform" described in the present invention refers to a cloud computing platform that comprehensively serves based on the hardware resources and software resources of the intelligent computing center.

[0037] The "intelligent computing center" described in the present invention includes, but is not limited to, the "intelligent computing center".

[0038] The "intelligent computing center" described in the present invention, that is, 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 using an artificial intelligence computing architecture.

[0039] 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, which has computing power, transportation power, and storage power, including general data centers, intelligent computing centers, supercomputing centers, etc.

[0040] 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 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.

[0041] 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.

[0042] 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.

[0043] The present invention provides a method for manually expanding and auditing computing power of an intelligent computing center cloud platform. Figure 1 The figure is a flow chart of a method for manually expanding and auditing the computing power of an intelligent computing center cloud platform of the present invention. The method for manually expanding and auditing the computing power of an intelligent computing center cloud platform includes: Step S1: receiving a capacity expansion instruction sent by a user through an interactive terminal, where the capacity expansion instruction includes: a computing power parameter adjusted by the user, a storage parameter adjusted by the user, and a network bandwidth parameter adjusted by the user; Step S2: According to the computing power parameters, storage parameters and network bandwidth parameters, review whether the expansion instruction meets the preset expansion rules and obtain the review result; Step S3: If the review result indicates that the expansion instruction meets the expansion rules, and the estimated computing power cost after the expansion does not exceed the preset budget threshold, the user's computing power is expanded according to the expansion instruction.

[0044] In the present invention, the capacity expansion instruction includes: user-adjusted computing power parameters, user-adjusted storage parameters, and user-adjusted network bandwidth parameters, breaking through the single resource dimension and realizing the linkage adjustment of computing power, storage, and network (for example, automatically expanding parallel storage IO bandwidth when GPUs are added).

[0045] In some embodiments of the present invention, computing power parameters may include: users adjusting computing power (GPU / CPU core number) in real time; storage parameters may include disk capacity; network bandwidth parameters are set values for network bandwidth, and network bandwidth refers to the ability to transmit data in a network, usually measured in terms of the amount of data transmitted per second, with units including bits per second (bps), kilobits per second (Kbps), megabits per second (Mbps), gigabits per second (Gbps), etc.

[0046] In some embodiments of the present invention, the preset capacity expansion rule may include: whether the computing power after expanding according to the computing power parameter, storage parameter, and network bandwidth parameter exceeds the total amount of resources that the user is permitted to call. If it does not exceed, the capacity expansion rule is satisfied; if it exceeds, the capacity expansion rule is not satisfied. It can be understood that the total amount of resources that the user is permitted to call can be pre-configured by the administrator.

[0047] In some embodiments of the present invention, the preset budget threshold may be the balance of the user's fund account for computing power market transactions; or it may be the sum of the balance of the user's fund account for computing power market transactions and the maximum overspending limit for the user in the computing power market transactions (although it exceeds the balance of the fund account, but within the maximum overspending limit, the computing power market transactions still support the user's computing power requirements). That is to say, the preset budget threshold actually represents the user's maximum payment ability in computing power market transactions.

[0048] In some embodiments of the present invention, the preset budget threshold may be the upper limit of expenditure set by the user according to their actual needs.

[0049] In the present invention, through step S3, when the audit result indicates that the capacity expansion instruction meets the capacity expansion rule, further, when the pre-estimated computing power cost after expansion does not exceed the preset budget threshold, the computing power of the user is expanded according to the capacity expansion instruction, avoiding the situation that the task running with the expanded computing power is suddenly interrupted due to insufficient funds, and improving the high reliability of computing power expansion.

[0050] In the present invention, through step S1: receiving a capacity expansion instruction sent by the user through the interaction terminal, the capacity expansion instruction includes: the computing power parameter adjusted by the user, the storage parameter adjusted by the user, and the network bandwidth parameter adjusted by the user; step S2: according to the computing power parameter, the storage parameter, and the network bandwidth parameter, auditing whether the capacity expansion instruction meets the preset capacity expansion rule to obtain an audit result; step S3: if the audit result indicates that the capacity expansion instruction meets the capacity expansion rule and the pre-estimated computing power cost after expansion does not exceed the preset budget threshold, expanding the computing power of the user according to the capacity expansion instruction, realizing the on-demand expansion of computing power for individual users, improving the flexibility of computing power allocation, and being beneficial to improving the utilization efficiency of computing power.

[0051] In some embodiments of the present invention, optionally, step S2 includes: Step S21: According to the computing power parameter, storage parameter, and network bandwidth parameter, determining whether the capacity expansion instruction is an abnormal instruction that exceeds the preset over-allocation threshold; Step S22: If the capacity expansion instruction is not an abnormal instruction, input the user's credit score, the user's historical computing power usage, the user's account balance information, computing power parameters, storage parameters, and network bandwidth parameters into a pre-trained audit model to obtain an audit result; Step S23: If the capacity expansion instruction is an abnormal instruction, generate a manual audit task and send the manual audit task to the administrator terminal associated with the administrator. Take the manual audit result obtained after the administrator terminal completes the manual audit task as the audit result.

[0052] In some embodiments of the present invention, the preset over-allocation threshold can be set by the administrator of the computing power of the intelligent computing center. In some embodiments, the over-allocation threshold can be specifically 300%. That is to say, when the computing power capacity required to be expanded by the capacity expansion instruction determined according to the computing power parameters, storage parameters, and network bandwidth parameters is over-allocated by more than 300%, it is determined that the capacity expansion instruction is an abnormal instruction. If the over-allocation of the computing power capacity required to be expanded is less than or equal to 300%, it is determined that the capacity expansion instruction is not an abnormal instruction.

[0053] In some embodiments of the present invention, the user's credit score can be a score for the degree of the user's compliance in applying computing power. Understandably, the fewer the number of error reports when the user applies computing power and the higher the computing power utilization rate, the higher the user's credit score.

[0054] In some embodiments of the present invention, the training process of the audit model may include: obtaining historical data of multiple users. The historical data of each user includes: credit score, historical computing power usage, account balance information, and the historical capacity expansion instructions sent by the user. Manually determine whether the preset capacity expansion rule is satisfied after executing the historical capacity expansion instruction, and label the user's historical data with the determination result. Aggregate all the historical data that has been labeled to obtain a training data set, and train the model with the training data set to obtain an audit model.

[0055] In the present invention, the combination of AI automatic approval (i.e., step S22) and manual review (i.e., step S23) takes into account both efficiency and security. In actual measurement, the audit delay is less than 5 seconds.

[0056] In some embodiments of the present invention, optionally, after step S2, it includes: Step S3': If the audit result indicates that the capacity expansion instruction does not meet the capacity expansion rule, terminate the capacity expansion, generate a first error message indicating that the capacity expansion instruction does not meet the capacity expansion rule, and send the first error message to the interaction terminal.

[0057] In the present invention, when the audit result indicates that the capacity expansion instruction does not meet the capacity expansion rule, the capacity expansion is terminated, a first error message indicating that the capacity expansion instruction does not meet the capacity expansion rule is generated, and the first error message is sent to the interaction terminal to prompt the user for the reason for terminating the capacity expansion, which is convenient for the user to adjust and modify, and improves the convenience of the user's operation of capacity expansion.

[0058] In some embodiments of the present invention, optionally, after step S2, it includes: Step S3'': When the audit result indicates that the expansion instruction meets the expansion rule, if the pre-estimated computing power cost after expansion exceeds the budget threshold, terminate the expansion, generate a second error message indicating that the budget threshold is exceeded, and send the second error message to the interaction end.

[0059] In the present invention, when the audit result indicates that the expansion instruction meets the expansion rule and the pre-estimated computing power cost after expansion exceeds the budget threshold, terminate the expansion, generate a second error message indicating that the budget threshold is exceeded, and send the second error message to the interaction end to prompt the user for the reason of terminating the expansion, which is convenient for the user to adjust and modify, and improves the convenience of the user's operation of expansion.

[0060] In some embodiments of the present invention, optionally, each user has an independent resource space divided by containerization technology; Step S3 includes: Step S31: Expand within the resource space corresponding to the user according to the expansion instruction.

[0061] In the present invention, containerization technology (e.g., Kubernetes) is used to allocate independent resource spaces for each user, and the resources are elastically scaled on demand to ensure that each user operates the expansion independently, improving the stability of the intelligent computing center.

[0062] In some embodiments of the present invention, optionally, step S3 includes: Step S32: Dynamically expand the network bandwidth through software-defined network.

[0063] In the present invention, the network bandwidth is dynamically divided by SDN (software-defined network) to avoid competition among multiple users.

[0064] The present invention provides a device for manual expansion and audit of computing power of an intelligent computing center cloud platform. Refer to Figure 2 as shown in Figure 2 is a schematic block diagram of the device for manual expansion and audit of computing power of the intelligent computing center cloud platform of the present invention. The device 20 for manual expansion and audit of computing power of the intelligent computing center cloud platform includes: A receiving module 21, configured to receive an expansion instruction sent by a user through an interaction end, where the expansion instruction includes: computing power parameters adjusted by the user, storage parameters adjusted by the user, and network bandwidth parameters adjusted by the user; An audit module 22, configured to audit whether the expansion instruction meets a preset expansion rule according to the computing power parameters, the storage parameters, and the network bandwidth parameters, and obtain an audit result; An execution module 23, configured to, if the audit result indicates that the capacity expansion instruction meets the capacity expansion rule and the pre-estimated computing power cost after capacity expansion does not exceed a preset budget threshold, expand the computing power of the user according to the capacity expansion instruction.

[0065] In some embodiments of the present invention, optionally, the audit module 22 is further configured to determine whether the capacity expansion instruction is an abnormal instruction that exceeds a preset over-allocation threshold according to the computing power parameter, the storage parameter, and the network bandwidth parameter; The audit module 22 is further configured to, if the capacity expansion instruction is not the abnormal instruction, input the user's credit score, the user's historical computing power usage, the user's account balance information, the computing power parameter, the storage parameter, and the network bandwidth parameter into a pre-trained audit model to obtain the audit result; The audit module 22 is further configured to, if the capacity expansion instruction is the abnormal instruction, generate an artificial audit task and send the artificial audit task to an administrator terminal associated with the administrator, and use the artificial audit result obtained after the administrator terminal completes the artificial audit task as the audit result.

[0066] In some embodiments of the present invention, optionally, the execution module 23 is further configured to, if the audit result indicates that the capacity expansion instruction does not meet the capacity expansion rule, terminate the capacity expansion, generate a first error message indicating that the capacity expansion instruction does not meet the capacity expansion rule, and send the first error message to the interaction terminal.

[0067] In some embodiments of the present invention, optionally, the execution module 23 is further configured to, when the audit result indicates that the capacity expansion instruction meets the capacity expansion rule, if the pre-estimated computing power cost after capacity expansion exceeds the budget threshold, terminate the capacity expansion, generate a second error message indicating that the budget threshold is exceeded, and send the second error message to the interaction terminal.

[0068] In some embodiments of the present invention, optionally, each user has an independent resource space divided by containerization technology; The execution module 23 is further configured to perform capacity expansion within the resource space corresponding to the user according to the capacity expansion instruction.

[0069] In some embodiments of the present invention, optionally, the execution module 23 is further configured to perform dynamic capacity expansion on the network bandwidth through software-defined networking.

[0070] The computing power manual expansion and audit device of the intelligent computing center cloud platform provided by the present invention can implement Figure 1 each process implemented by the method embodiments and achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0071] The present invention provides an electronic device 30. Refer to Figure 3 as shown in Figure 3 which is a schematic block diagram of the electronic device 30 of the present invention, including a processor 31, a memory 32, and a program or instruction stored in the memory 32 and executable on the processor 31. When the program or instruction is executed by the processor, the steps in any of the methods for manually expanding and auditing the computing power of the intelligent computing center cloud platform of the present invention are implemented.

[0072] The present invention provides a readable storage medium with a program or instruction stored thereon. When the program or instruction is executed by a processor, the various processes of the embodiments of the method for manually expanding and auditing the computing power of the intelligent computing center cloud platform as described above are implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0073] Among them, the readable storage medium includes, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc. In some examples, the readable storage medium may be a non-transitory readable storage medium.

[0074] The present invention also provides a computer program product including computer instructions. When the computer instructions are executed by a processor, the various processes of the embodiments of the method for manually expanding and auditing the computing power of the intelligent computing center cloud platform as described above are implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0075] 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 explicitly listed, or further includes elements inherent to such a process, method, article, or device. Without further limitations, 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.

[0076] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the purpose of the present invention and the scope protected by the claims, and all of them belong to the protection scope of the present invention.

Claims

1. A method for manual expansion and review of computing power of an intelligent computing center cloud platform, characterized in that, including: Step S1: Receive an expansion instruction sent by the user through the interaction terminal. The expansion instruction includes: the computing power parameters adjusted by the user, the storage parameters adjusted by the user, and the network bandwidth parameters adjusted by the user; Step S2: According to the computing power parameters, the storage parameters, and the network bandwidth parameters, review whether the expansion instruction meets the preset expansion rules to obtain a review result; Step S3: If the review result indicates that the expansion instruction meets the expansion rules and the pre-estimated computing power cost after expansion does not exceed the preset budget threshold, expand the user's computing power according to the expansion instruction.

2. The method for manual expansion and audit of computing power of the intelligent computing center cloud platform according to claim 1, characterized in that The step S2 includes: Step S21: According to the computing power parameters, the storage parameters, and the network bandwidth parameters, determine whether the expansion instruction is an abnormal instruction that exceeds the preset over-allocation threshold; Step S22: If the expansion instruction is not the abnormal instruction, input the user's credit score, the user's historical computing power usage, the user's account balance information, the computing power parameters, the storage parameters, and the network bandwidth parameters into a pre-trained review model to obtain the review result; Step S23: If the expansion instruction is the abnormal instruction, generate an artificial review task and send the artificial review task to the administrator terminal associated with the administrator. Use the artificial review result obtained after the administrator terminal completes the artificial review task as the review result.

3. The method for manual expansion and audit of computing power of the intelligent computing center cloud platform according to claim 1, wherein, After the step S2 includes: Step S3’: If the review result indicates that the expansion instruction does not meet the expansion rules, terminate the expansion, generate a first error message indicating that the expansion instruction does not meet the expansion rules, and send the first error message to the interaction terminal.

4. The method for manual expansion and review of computing power of the intelligent computing center cloud platform according to claim 1, wherein After the step S2 includes: Step S3’’: In the case where the review result indicates that the expansion instruction meets the expansion rules, if the pre-estimated computing power cost after expansion exceeds the budget threshold, terminate the expansion, generate a second error message indicating that it exceeds the budget threshold, and send the second error message to the interaction terminal.

5. The method for manual expansion and audit of computing power of the intelligent computing center cloud platform according to claim 1, characterized in that, Each user has an independent resource space divided by containerization technology; The step S3 includes: Step S31: Expand within the resource space corresponding to the user according to the expansion instruction.

6. The method for manual expansion and audit of computing power of the intelligent computing center cloud platform according to claim 1 or 5, characterized in that, The step S3 includes: Step S32: Dynamically expand the network bandwidth through software-defined networking.

7. An arithmetic power manual expansion and auditing device for an intelligent computing center cloud platform, characterized in that, including: A receiving module, configured to receive an expansion instruction sent by the user through the interaction terminal. The expansion instruction includes: the computing power parameters adjusted by the user, the storage parameters adjusted by the user, and the network bandwidth parameters adjusted by the user; A review module, configured to review whether the expansion instruction meets the preset expansion rules according to the computing power parameters, the storage parameters, and the network bandwidth parameters to obtain a review result; An execution module, configured to expand the user's computing power according to the expansion instruction if the review result indicates that the expansion instruction meets the expansion rules and the pre-estimated computing power cost after expansion does not exceed the preset budget threshold.

8. An electronic device, characterized in that: It includes a processor, a memory, and programs or instructions stored on the memory and executable on the processor. When the programs or instructions are executed by the processor, the steps in the method for manual expansion and review of computing power of the intelligent computing center cloud platform as described in any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized in that: Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by the processor, the steps in the method for manual expansion and review of computing power of the intelligent computing center cloud platform as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that, It includes computer instructions. When the computer instructions are executed by the processor, the steps of the method for manual expansion and review of computing power of the intelligent computing center cloud platform as described in any one of claims 1 to 6 are implemented.

Images