Computing power resource storage method and device of intelligent computing center

Abstract

The invention provides a computing power resource storage method and device of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructure, the method comprises the following steps: S1, receiving target data, the target data being data to be stored by a user; s2, the target data is stored in a set storage space, the set storage space is the data storage space of a storage management system, the storage management system comprises a plurality of storage devices, and the data storage capacity of the set storage space is the storage capacity of the PB level of ten trillion bytes. According to the invention, the storage management system is formed by the plurality of storage devices, so that the magnitude breakthrough of the storage capacity of the data storage space is realized by superposing the data storage space of the plurality of storage devices, and the storage management system can support the storage capacity of a PB level; therefore, the data storage requirement of the continuously increasing computing power resources of the intelligent computing center is met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent computing centers, wisdom computing centers and computing power infrastructure, and in particular to a computing power resource storage method and device for an intelligent computing center. BACKGROUND

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

[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, to provide the required computing power, data and algorithms for artificial intelligence applications, such as artificial intelligence deep learning model development, model training and model inference scenarios. An intelligent computing center covers facilities, hardware and software, and can provide full-stack capabilities from bottom computing power to top application enablement.

[0004] An intelligent computing center includes, but is not limited to, a wisdom computing center.

[0005] A wisdom computing center, also known as an artificial intelligence computing center, is a type of computing power infrastructure that provides computing power services, data services and algorithm services required by artificial intelligence applications based on artificial intelligence theory and artificial intelligence computing architecture.

[0006] Computing power is the core of an intelligent computing center and a wisdom computing center, and is the ability of a computer device or computing / data center to process information. It is the ability of computer hardware and software to jointly execute certain computing requirements, and is the computing power that achieves 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 power, and mainly provides services to society through computing power infrastructure.

[0007] Currently, an intelligent computing center of the prior art can at most support Terabyte (TB) level data storage, and cannot support Petabyte (PB) or even higher level data storage. SUMMARY

[0008] The present application aims to provide an intelligent computing center computing power resource storage method and device to solve the technical problem that the prior art cannot support PB level data storage.

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

[0010] In a first aspect, the present application provides an intelligent computing center computing power resource storage method, which comprises:

[0011] Step S1, receiving target data, wherein the target data is data to be stored by a user;

[0012] Step S2, storing the target data in a set storage space, wherein the set storage space is a data storage space of a storage management system, the storage management system comprises a plurality of storage devices, and a data storage capacity of the set storage space is a storage capacity of a petabyte PB level.

[0013] In one embodiment, the step S2 comprises:

[0014] Step S21, determining a target sub-space associated with a user corresponding to the target data in a plurality of sub-spaces of the set storage space;

[0015] Step S22, when an available capacity value of the target sub-space is greater than or equal to a target capacity value, storing the target data in the target sub-space, wherein the target capacity value is a size of a storage space required by the target data to occupy;

[0016] Step S23, when the available capacity value of the target sub-space is less than the target capacity value, terminating a storage operation of the target data, and outputting prompt information, wherein the prompt information at least comprises the available capacity value and the target capacity value.

[0017] In one embodiment, the target sub-space comprises a first storage space and a second storage space, and a data storage efficiency of the first storage space is higher than a data storage efficiency of the second storage space;

[0018] The step S22 comprises:

[0019] Step S221, when the available capacity value is greater than or equal to the target capacity value, and the target data satisfies a target condition, storing the target data in the target sub-space based on a first rule, wherein the first rule is that a data storage priority of the first storage space is higher than a data storage priority of the second storage space;

[0020] Step S222, when the available capacity value is greater than or equal to the target capacity value, and the target data does not satisfy the target condition, storing the target data in the target sub-space based on a second rule, wherein the second rule is that the data storage priority of the second storage space is higher than the data storage priority of the first storage space;

[0021] The target condition comprises that a usage frequency of the target data is higher than a set frequency, and / or a data priority of the target data is higher than a set priority.

[0022] In an embodiment, before the step S221, the method further comprises:

[0023] The step S220, in a plurality of data formats preset, determining a target data format corresponding to the target data, and determining a data usage frequency of the target data format as the usage frequency of the target data, and determining a data priority of the target data format as the data priority of the target data.

[0024] In an embodiment, after the step S2, the method comprises:

[0025] The step S3, generating and outputting capacity usage information according to the used capacity value and the maximum capacity value, wherein the capacity usage information comprises a capacity usage rate and prompt information, the capacity usage rate is a ratio of the used capacity value and the maximum capacity value, the used capacity value is a size of the occupied storage space in the set storage space, the maximum capacity value is a size of the set storage space, and the prompt information is used to indicate whether the capacity usage rate is less than a first threshold value and / or whether the capacity usage rate is greater than a second threshold value, the first threshold value is less than the second threshold value.

[0026] In an embodiment, after the step S2, the method comprises:

[0027] The step S4, sampling the target data in the set storage space based on a set sampling rule to obtain a plurality of first data points;

[0028] The step S5, performing data consistency detection based on the plurality of first data points and a plurality of second data points to obtain detection information, wherein the plurality of second data points are sampled from backup data based on the set sampling rule, the backup data is a data backup corresponding to the target data, and the plurality of second data points and the plurality of first data points correspond one by one;

[0029] The step S6, in a case where the detection information indicates that the plurality of first data points and the plurality of second data points satisfy a consistency condition, deleting the backup data;

[0030] The step S7, in a case where the detection information indicates that the plurality of first data points and the plurality of second data points do not satisfy the consistency condition, deleting the target data in the set storage space and storing the backup data in the set storage space;

[0031] Wherein, the plurality of first data points and the plurality of second data points satisfying the consistency condition comprises: in the plurality of first data points, data included in each of the first data points and data included in the corresponding second data point are the same.

[0032] In a second aspect, the present application further provides a computing power resource storage device of an intelligent computing center, the device comprising:

[0033] a data receiving module configured to receive target data, wherein the target data is data to be stored by a user;

[0034] a data storage module configured to store the target data in a set storage space, wherein the set storage space is a data storage space of a storage management system, the storage management system comprises a plurality of storage devices, and the data storage capacity of the set storage space is a storage capacity of a petabyte (PB) level.

[0035] In a third aspect, the present application further provides a server, comprising a processor, a memory, and a program stored in the memory and executable in the processor, wherein the program, when executed by the processor, implements the steps of the computing power resource storage method of the intelligent computing center according to the first aspect.

[0036] In a fourth aspect, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps of the computing power resource storage method of the intelligent computing center according to the first aspect.

[0037] In a fifth aspect, the present application provides a computer program product comprising computer instructions, wherein the computer instructions, when executed by a processor, implement the steps of the computing power resource storage method of the intelligent computing center according to the first aspect.

[0038] In the present application, a plurality of storage devices are used to form a storage management system, so as to realize a magnitude breakthrough of the storage capacity of the data storage space by stacking the data storage spaces of the plurality of storage devices, so that the storage management system can support a storage capacity of a petabyte (PB) level, thereby meeting the data storage demand of the growing computing power resource of the intelligent computing center. BRIEF DESCRIPTION OF DRAWINGS

[0039] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments, and are not intended to limit the scope of the present application. Moreover, like reference numerals designate like parts throughout the several views in the drawings. In the drawings:

[0040] Figure 1 is a flowchart of a computing power resource storage method of an intelligent computing center provided by the present application;

[0041] Figure 2It is a structural schematic diagram of an intelligent computing center's computing resource storage device provided by the application.

[0042] Figure 3 It is a structural schematic diagram of an electronic device provided by the application. DETAILED DESCRIPTION

[0043] The technical solutions in the application will be clearly and completely described below with reference to the drawings in the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0044] The technical terms related to the application will be simply described below.

[0045] The "computing power" in the application refers to the ability of a computer device or a computing / data center to process information, the ability of computer hardware and software to jointly perform certain computing requirements, the computing ability to realize target result output by processing information data, and the new productivity integrating information computing power, network carrying power and data storage power, which mainly provides services to the society through computing power infrastructure.

[0046] The "computing power" (Computational Power, CP) in the application refers to the ability of a data center server to process data and realize result output, which is a comprehensive index for measuring the computing power of a data center, including general computing power, supercomputing power and intelligent computing power. The commonly used unit of measurement is the number of floating point operations per second (FLOPS, 1EFLOPS=10^18FLOPS), and the larger the value is, the stronger the comprehensive computing power is. According to the estimation, 1EFLOPS is about the computing power output of 5 Tianhe 2A, 500,000 mainstream server CPUs or 2,000,000 mainstream notebooks. The calculation formula is: CP=CPgeneral+CPintelligent+CPsuper.

[0047] The "carrying power" (Network Power, NP) in the application refers to the performance of the data transmission ability of computing power infrastructure, including the comprehensive ability of network architecture, network bandwidth, transmission delay, intelligent management and scheduling, and involves the network transmission between the data center and the data center, which is a comprehensive index for measuring the network transmission scheduling ability.

[0048] The "storage power" (SP) described in the application refers to the comprehensive ability of a data center in four aspects of data storage capacity, performance, safety and reliability, and green and low carbon, which is a comprehensive index for measuring the data storage capacity of a data center, and includes external storage devices such as storage arrays and built-in storage devices of servers. The commonly used unit of measurement for storage capacity is exabyte (EB, 1 EB = 2^60 bytes), the commonly used unit of measurement 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 performance of safety and reliability.

[0049] The "computing power infrastructure" described in the application refers to a new type of information infrastructure integrating information computing power, network carrying capacity and data storage power, which can realize centralized computing, storage, transmission and application of information.

[0050] The "new type of information infrastructure" described in the application refers to network infrastructure mainly including 5G network, fiber broadband network, backbone network, international communication network, satellite Internet, etc., computing power infrastructure including data center, general computing center, intelligent computing center, supercomputing center, etc., and new technology infrastructure including artificial intelligence, blockchain, quantum computing, etc.

[0051] The "computing power" described in the application includes general computing power, intelligent computing power and supercomputing power.

[0052] The "general computing power" described in the application refers to the computing power provided by a server based on a CPU (Central Processing Unit) chip, which is used to support basic general computing such as cloud computing and edge computing.

[0053] The "intelligent computing power" described in the application refers to the large-scale deployment of computing platforms based on GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array) and ASIC (Application Specific Integrated Circuit) special chips for various artificial intelligence innovation applications, such as natural language processing and machine vision.

[0054] The "supercomputing power" described in the application refers to the computing power provided by a supercomputer and other high-performance computing clusters, which utilizes centralized computing resources of multiple computer systems working in parallel and processes extremely complex or data-intensive problems through a dedicated operating system, mainly used for computing in cutting-edge scientific fields such as planet simulation, drug molecule design and gene analysis.

[0055] The "intelligent computing center" described in the present application refers to: by using large-scale heterogeneous computing resources, including general computing power (CPU) and intelligent computing power (GPU, FPGA, ASIC, etc.), mainly providing the required computing power, data and algorithms for artificial intelligence applications (such as artificial intelligence deep learning model development, model training and model inference, etc. Scene) facilities. The intelligent computing center covers facilities, hardware, software, and can provide full-stack capabilities from bottom computing to top application enablement.

[0056] The "intelligent computing center" described in the present application includes but is not limited to "intelligent computing center".

[0057] The "intelligent computing center" described in the present application, namely the artificial intelligence computing center, is based on artificial intelligence theory, adopts artificial intelligence computing architecture, and provides artificial intelligence application required computing power service, data service and algorithm service. A kind of computing power infrastructure.

[0058] The "computing power center" described in the present application refers to: taking infrastructure such as wind, fire, water and electricity and IT hardware and software equipment as the main component, with computing power, carrying capacity and storage capacity. Facilities, including general data centers, intelligent computing centers, supercomputing centers, etc.

[0059] The "supercomputing center" described in the present application refers to: supercomputing data center, which is based on supercomputer or large-scale computing cluster data center, which can provide large-scale computing, storage and network services, etc. Function, widely used in aerospace, national defense, oil exploration, climate modeling and genome sequencing, etc. Application scenarios.

[0060] The "computing power resource" described in the present application refers to: the technology and facilities required for the development of digital society, which have information computing, transmission, storage and application capabilities, including but not limited to CPU, GPU, etc. Computing resource switch, router, etc. Network resources, storage arrays, distributed storage, etc. Storage resources, firewalls, intrusion detection systems, etc. Security resources, and supporting resources such as wind, fire, water and electricity.

[0061] The "model" described in the present application includes but is not limited to "large language model" and "multimodal large model".

[0062] The "large language model" described in the present application refers to a large-scale language model (large language model, LLM), which is a language model with a large number of parameters. It aims to understand and generate human language, and is trained through a large amount of text data. It can perform a wide range of tasks including text summarization, translation, sentiment analysis, etc.

[0063] The'multimodal large model' in the present application refers to a model trained by combining multimodal information such as text, image, video and audio, including but not limited to a multimodal large language model.

[0064] Please refer to Figure 1 , Figure 1 The application provides an intelligent computing center computing resource storage method, as shown in Figure 1 , comprising the following steps:

[0065] Step S1, receiving target data.

[0066] The target data is the data to be stored by the user. For example, the target data can be model architecture data, sample data for training or fine-tuning the model, or result data output after processing business data by the model, etc.

[0067] Step S2, storing the target data in a set storage space.

[0068] The set storage space is the data storage space of the storage management system, the storage management system includes a plurality of storage devices, and the data storage capacity of the set storage space is a storage capacity of the order of petabyte (PB).

[0069] The storage device can include a hard disk drive (HDD), a solid state drive (SSD), etc.

[0070] For example, the storage management system can be a distributed storage system, in which case the plurality of storage devices can be understood as a plurality of distributed storage nodes in the distributed storage system. Based on this setting, the dynamic expansion of the data storage capacity of the storage management system can be flexibly realized to adapt to the growing data storage needs of the computing power resources of the intelligent computing center.

[0071] The storage capacity of the order of PB can be understood as a data storage capacity greater than or equal to 1PB.

[0072] In one example, after the storage management system is constructed based on the plurality of storage devices, 1PB of test data prepared in advance can be written into the set storage space. When the test data is successfully written, it can be determined that the data storage capacity of the set storage space reaches the order of PB.

[0073] In the present application, a plurality of storage devices are used to constitute a storage management system, so as to realize a magnitude breakthrough of the storage capacity of the data storage space by stacking the data storage spaces of the plurality of storage devices, so that the storage management system can support a PB-level storage capacity, thereby meeting the data storage demand of the growing computing power resources of the intelligent computing center.

[0074] In one embodiment, the step S2 comprises:

[0075] Step S21, in the plurality of subspaces of the set storage space, a target subspace associated with a user corresponding to the target data is determined;

[0076] Step S22, when the available capacity value of the target subspace is greater than or equal to a target capacity value, the target data is stored in the target subspace, wherein the target capacity value is the size of the storage space required by the target data to occupy;

[0077] Step S23, when the available capacity value of the target subspace is less than the target capacity value, the storage operation of the target data is terminated, and a prompt information is outputted, wherein the prompt information at least includes the available capacity value and the target capacity value.

[0078] It is to be noted that in the application, the storage management system accesses a plurality of users, in order to better manage the data stored by the plurality of users, and to protect the independence between the data stored by different users, that is, a plurality of subspaces are divided in the set storage space to correspond to the plurality of users respectively, and the data of each user is stored in the subspace corresponding thereto.

[0079] Exemplarily, the same size of subspace can be equally allocated to the plurality of users; the corresponding subspace size can be manually specified by the user when the user accesses the storage management system for the first time; or the corresponding subspace size can be automatically determined by analyzing the business information of the user (including the business field, the business data volume per unit time, etc.).

[0080] The target subspace associated with the user corresponding to the target data can be understood as: the subspace allocated to the user corresponding to the target data in the set storage space.

[0081] The prompt information is used to prompt the user that the currently available data storage space of the target subspace is insufficient to completely store the target data.

[0082] In this embodiment, based on the above setting, in the case that the target data is too large to be completely stored in the subspace corresponding to the user, the storage operation of the target data is timely prevented, so as to avoid the loss and incompleteness of the target data in the storage process, and to improve the user experience of the storage management system.

[0083] In one embodiment, the target subspace comprises a first storage space and a second storage space, and the data storage efficiency of the first storage space is higher than that of the second storage space.

[0084] The step S22 comprises:

[0085] Step S221, when the available capacity value is greater than or equal to the target capacity value, and the target data meets the target condition, storing the target data into the target subspace based on a first rule, wherein the first rule is that the data storage priority of the first storage space is higher than that of the second storage space.

[0086] Step S222, when the available capacity value is greater than or equal to the target capacity value, and the target data does not meet the target condition, storing the target data into the target subspace based on a second rule, wherein the second rule is that the data storage priority of the second storage space is higher than that of the first storage space.

[0087] The target condition comprises that the usage frequency of the target data is higher than a set frequency, and / or the data priority of the target data is higher than a set priority.

[0088] The target data not meeting the target condition can be understood as that the usage frequency of the target data is less than or equal to the set frequency, and the data priority of the target data is less than or equal to the set priority.

[0089] The data storage efficiency of the first storage space being higher than that of the second storage space can be understood as that, for the same data, the time consumption of the first storage space in storing the data is less than that of the second storage space, and the time consumption of the first storage space in reading the data is less than that of the second storage space.

[0090] The data priority is used to represent the importance of the corresponding data, or the urgency in terms of time effectiveness of the corresponding data. For example, the privacy data related to the identity of the customer belongs to data with high importance, and the private data within the organization also belongs to data with high importance; the data with time limit for use (for example, valid within 30 minutes) belongs to data with high urgency in terms of time effectiveness.

[0091] It is to be noted that the first rule specifically is that the data to be stored is first stored in the first storage space until the first storage space is full; if the first storage space is full and there is still a remaining part of the data to be stored, the remaining part is stored in the second storage space.

[0092] Similarly, the second rule is specifically: the data to be stored is first stored in the second storage space until the second storage space is full; if the second storage space is full and there is still a remaining part of the data to be stored, then the remaining part is stored in the first storage space.

[0093] In this embodiment, based on the setting of the set frequency, it is determined whether the target data belongs to high-frequency use data (the use frequency is higher than the set frequency) or non-high-frequency use data (the use frequency is less than or equal to the set frequency); based on the setting of the set priority, it is determined whether the target data belongs to critical data (the data priority is higher than the set priority) or non-critical data (the data priority is less than or equal to the set priority); and when the target data belongs to high-frequency use data and / or critical data, the first storage space with higher data storage efficiency is used to store the target data first, so as to provide more efficient data read-write support for high-frequency use data and / or critical data; and when the target data does not belong to high-frequency use data and / or critical data, the second storage space with lower data storage efficiency is used to store the target data first, so as to provide relatively low-efficient data read-write support for data that is neither high-frequency use data nor critical data, and to reserve sufficient storage space with efficient read-write capability for possible high-frequency use data and / or critical data.

[0094] It should be noted that in the application, the plurality of data stored in the first storage space needs to be periodically monitored, so that when it is monitored that part of the data stored in the first storage space does not meet the target condition, the part of the data that no longer meets the target condition is transferred from the first storage space to the second storage space in an asynchronous manner, so that the first storage space with higher data storage efficiency is effectively used on the premise of ensuring the integrity of the data stored in the target sub-space.

[0095] For example, if a certain data A in the first storage space meets the foregoing target condition in the previous monitoring period, and in the current monitoring period, the data A no longer meets the target condition, then the data A needs to be transferred from the first storage space to the second storage space in an asynchronous manner, so as to release the storage resources occupied by the data A in the first storage space, and to leave sufficient storage resources in the first storage space for critical data and / or high-frequency use data.

[0096] In one embodiment, before the step S221, the method further comprises:

[0097] In step S220, a target data format corresponding to the target data is determined from the plurality of data formats, and a data usage frequency of the target data format is determined as the usage frequency of the target data, and a data priority of the target data format is determined as the data priority of the target data.

[0098] For example, the plurality of data formats include a first data format corresponding to a model structure, a second data format corresponding to a model sample, and a third data format corresponding to a model processing result.

[0099] For example, the metadata of the target data, such as data notes and data description information, can be used to determine the target data format from the plurality of data formats.

[0100] It should be noted that the data usage frequency of each data format in the plurality of data formats can be obtained by counting the usage records of the corresponding data in the historical period; similarly, the data priority of each data format can be the highest data priority of the corresponding data in the historical period.

[0101] In this embodiment, the usage frequency of the target data and the data priority of the target data are determined by classifying the data format of the target data, so as to reduce the interference of human factors, and make the determined usage frequency of the target data and the data priority of the target data more accurate and reliable.

[0102] In one embodiment, after step S2, the method comprises:

[0103] In step S3, capacity usage information is generated and output according to the used capacity value and the maximum capacity value, wherein the capacity usage information includes a capacity usage rate and prompt information, the capacity usage rate is a ratio of the used capacity value and the maximum capacity value, the used capacity value is a size of the occupied storage space in the set storage space, the maximum capacity value is a size of the set storage space, and the prompt information is used to indicate whether the capacity usage rate is less than a first threshold value and / or whether the capacity usage rate is greater than a second threshold value, the first threshold value is less than the second threshold value.

[0104] For example, the first threshold value can be 5%, and the second threshold value can be 80%.

[0105] In this embodiment, the output of the capacity usage information prompts the administrator of the storage management system to set whether the current capacity usage of the storage space is too large or too small, thereby helping the administrator to better monitor the capacity usage of the storage space, so that the administrator can timely expand the capacity or limit data storage when the capacity of the storage space is insufficient (whether the capacity usage is greater than the second threshold value), and timely take measures to stimulate the user's data storage demand when the capacity of the storage space is idle (whether the capacity usage is less than the first threshold value).

[0106] In one embodiment, after the step S2, the method comprises:

[0107] Step S4, sampling the target data in the set storage space based on a set sampling rule to obtain a plurality of first data points;

[0108] Step S5, performing data consistency detection based on the plurality of first data points and a plurality of second data points to obtain detection information, wherein the plurality of second data points are sampled from backup data based on the set sampling rule, the backup data is a data backup corresponding to the target data, and the plurality of second data points and the plurality of first data points correspond one by one;

[0109] Step S6, deleting the backup data when the detection information indicates that the plurality of first data points and the plurality of second data points satisfy a consistency condition;

[0110] Step S7, deleting the target data in the set storage space and storing the backup data in the set storage space when the detection information indicates that the plurality of first data points and the plurality of second data points do not satisfy the consistency condition;

[0111] Wherein, the plurality of first data points and the plurality of second data points satisfying the consistency condition includes: in the plurality of first data points, the data included in each first data point and the data included in the corresponding second data point are the same.

[0112] It is to be noted that the plurality of first data points and the plurality of second data points are sampled by the same sampling rule (i.e. the set sampling rule), that is, in the plurality of first data points, the sampling position of each first data point in the target data and the sampling position of the corresponding second data point in the backup data are the same. For example, if a first data point is sampled from position X in the target data, then the corresponding second data point is sampled from position X in the backup data.

[0113] In this embodiment, based on the above setting, it is detected whether the target data is correctly stored in the set storage space by the existence of backup data in combination with the sampling mode, and when it is detected that the target data is not correctly stored in the set storage space (i.e. the plurality of first data points and the plurality of second data points do not satisfy the consistency condition), the re-storage of the target data in the set storage space is completed based on the backup data to guarantee the reliable storage of the target data in the set storage space as much as possible.

[0114] Please refer to Figure 2 , Figure 2 is a structural diagram of an intelligent computing center's computing resource storage device provided by the present application, as shown in Figure 2 The intelligent computing center's computing resource storage device 200 includes:

[0115] A data receiving module 201 is configured to receive target data, wherein the target data is data to be stored by a user.

[0116] A data storage module 202 is configured to store the target data in a set storage space, wherein the set storage space is a data storage space of a storage management system, the storage management system includes a plurality of storage devices, and the data storage capacity of the set storage space is a storage capacity of a petabyte (PB) level.

[0117] In one embodiment, the data storage module 202 includes:

[0118] A sub-space determining unit is configured to determine a target sub-space associated with a user corresponding to the target data in a plurality of sub-spaces of the set storage space.

[0119] A data storage unit is configured to store the target data in the target sub-space when an available capacity value of the target sub-space is greater than or equal to a target capacity value, wherein the target capacity value is the size of the storage space required by the target data.

[0120] The data storage unit is further configured to terminate the storage operation of the target data and output a prompt information when the available capacity value of the target sub-space is less than the target capacity value, wherein the prompt information at least includes the available capacity value and the target capacity value.

[0121] In one embodiment, the target sub-space includes a first storage space and a second storage space, and the data storage efficiency of the first storage space is higher than that of the second storage space.

[0122] The data storage unit is specifically configured to:

[0123] when the available capacity value is greater than or equal to the target capacity value and the target data meets the target condition, storing the target data into the target subspace based on a first rule, wherein the first rule is that a data storage priority of the first storage space is higher than a data storage priority of the second storage space;

[0124] when the available capacity value is greater than or equal to the target capacity value and the target data does not meet the target condition, storing the target data into the target subspace based on a second rule, wherein the second rule is that the data storage priority of the second storage space is higher than the data storage priority of the first storage space;

[0125] The target condition includes that a usage frequency of the target data is higher than a set frequency, and / or a data priority of the target data is higher than a set priority.

[0126] In an embodiment, the data storage unit is further configured to:

[0127] In a plurality of preset data formats, determine a target data format corresponding to the target data, and determine a data usage frequency of the target data format as the usage frequency of the target data, and determine a data priority of the target data format as the data priority of the target data.

[0128] In an embodiment, the computing power resource storage device 200 of the intelligent computing center further includes:

[0129] An information prompting module is configured to generate and output capacity usage information according to the used capacity value and the maximum capacity value, wherein the capacity usage information includes a capacity usage rate and a prompt information, the capacity usage rate is a ratio of the used capacity value and the maximum capacity value, the used capacity value is a size of a storage space occupied in the set storage space, the maximum capacity value is a size of the set storage space, and the prompt information is used to indicate whether the capacity usage rate is less than a first threshold value and / or whether the capacity usage rate is greater than a second threshold value, the first threshold value is less than the second threshold value.

[0130] In an embodiment, the computing power resource storage device 200 of the intelligent computing center further includes a data verification module, and the data verification module is specifically configured to:

[0131] Based on a set sampling rule, sample the target data in the set storage space to obtain a plurality of first data points;

[0132] perform data consistency detection based on the plurality of first data points and a plurality of second data points, to obtain detection information, wherein the plurality of second data points are obtained by sampling the backup data based on the set sampling rule, the backup data is a data backup corresponding to the target data, and the plurality of second data points and the plurality of first data points correspond to each other one by one;

[0133] in a case where the detection information indicates that the plurality of first data points and the plurality of second data points satisfy a consistency condition, deleting the backup data;

[0134] in a case where the detection information indicates that the plurality of first data points and the plurality of second data points do not satisfy the consistency condition, deleting the target data in the set storage space and storing the backup data in the set storage space;

[0135] wherein the plurality of first data points and the plurality of second data points satisfying the consistency condition comprises that, in the plurality of first data points, data included in each of the first data points is the same as data included in the corresponding second data point.

[0136] The computing power resource storage device of the intelligent computing center provided by the application corresponds to each process of each embodiment of the computing power resource storage method of the intelligent computing center described above, and can achieve the same technical effects. To avoid repetition, it will not be repeated here.

[0137] It should be noted that the computing power resource storage device of the intelligent computing center in the application can be a device, a component in an electronic device, an integrated circuit, or a chip.

[0138] The application also provides an electronic device, referring to Figure 3 , Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the application. The electronic device comprises a memory 301, a processor 302, and a program or instruction stored in the memory 301 and running on the memory 301. When the program or instruction is executed by the processor 302, it can realize Figure 1 Any step in the corresponding embodiment of the computing power resource storage method of the intelligent computing center and the same beneficial effects can be achieved, and here it will not be repeated.

[0139] The processor 302 can be a CPU, an ASIC, an FPGA, or a GPU.

[0140] A person of ordinary skill in the art can understand that all or part of the steps of the above-mentioned embodiment of the computing power resource storage method of the intelligent computing center can be completed by program instruction related hardware. The program can be stored in a readable medium.

[0141] The application further provides a readable storage medium, and the readable storage medium stores a computer program. Figure 1 Any step in the corresponding intelligent computing center computing resource storage method embodiment can achieve the same technical effect, and to avoid repetition, it is not described here. The storage medium, such as read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

[0142] The terms "first", "second", and the like in the present application are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or node including a series of steps or units does not necessarily limit to those clearly listed steps or units, but can include other steps or units not clearly listed or inherent to these processes, methods, products or nodes. In addition, "and / or" is used in the present application to represent at least one of the connected objects, for example, A and / or B and / or C, which represents 7 cases including A alone, B alone, C alone, A and B, B and C, A and C, and A, B and C.

[0143] It should be noted that in this paper, the term "include", "contain" or any other variation thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0144] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and necessary general hardware platform, of course, they can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions 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 plurality of instructions for making a terminal (which can be a mobile phone, computer, server, air conditioner, or second terminal node, etc.) execute the method of each embodiment of the present application.

[0145] The embodiments of the present application are described above with reference to the accompanying drawings, but the present application is not limited to the above-described specific embodiments, and the above-described specific embodiments are merely illustrative, but not restrictive, and a person of ordinary skill in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection of the present application.

Claims

1. A method for storing computing resources in an intelligent computing center, characterized in that, The method includes: Step S1: Receive target data, wherein the target data is data to be stored by the user; Step S2: Store the target data in a designated storage space, wherein the designated storage space is the data storage space of the storage management system, the storage management system includes multiple storage devices, and the data storage capacity of the designated storage space is at the petabyte level.

2. The method according to claim 1, characterized in that, Step S2 includes: Step S21: Among the multiple subspaces of the set storage space, determine the target subspace associated with the user corresponding to the target data; Step S22: When the available capacity value of the target subspace is greater than or equal to the target capacity value, the target data is stored in the target subspace, wherein the target capacity value is the size of the storage space required by the target data. Step S23: When the available capacity value of the target subspace is less than the target capacity value, terminate the storage operation of the target data and output a prompt message, wherein the prompt message includes at least the available capacity value and the target capacity value.

3. The method according to claim 2, characterized in that, The target subspace includes a first storage space and a second storage space, wherein the data storage efficiency of the first storage space is higher than that of the second storage space. Step S22 includes: Step S221: When the available capacity value is greater than or equal to the target capacity value, and the target data meets the target conditions, the target data is stored in the target subspace based on the first rule, wherein the first rule is: the data storage priority of the first storage space is higher than the data storage priority of the second storage space. Step S222: When the available capacity value is greater than or equal to the target capacity value, and the target data does not meet the target condition, the target data is stored in the target subspace based on the second rule, wherein the second rule is: the data storage priority of the second storage space is higher than the data storage priority of the first storage space. The target conditions include: the frequency of use of the target data is higher than the set frequency, and / or the data priority of the target data is higher than the set priority.

4. The method according to claim 3, characterized in that, Prior to step S221, the method further includes: Step S220: Among a plurality of pre-set data formats, determine the target data format corresponding to the target data, determine the data usage frequency of the target data format as the usage frequency of the target data, and determine the data priority of the target data format as the data priority of the target data.

5. The method according to claim 1, characterized in that, After step S2, the method includes: Step S3: Generate and output capacity usage information based on the used capacity value and the maximum capacity value. The capacity usage information includes a capacity usage rate and a prompt message. The capacity usage rate is the ratio of the used capacity value to the maximum capacity value. The used capacity value is the size of the occupied storage space within the set storage space. The maximum capacity value is the size of the set storage space. The prompt message indicates whether the capacity usage rate is less than a first threshold and / or whether the capacity usage rate is greater than a second threshold, wherein the first threshold is less than the second threshold.

6. The method according to claim 1, characterized in that, After step S2, the method includes: Step S4: Based on the set sampling rules, sample the target data in the set storage space to obtain multiple first data points; Step S5: Perform data consistency detection based on the plurality of first data points and the plurality of second data points to obtain detection information. The plurality of second data points are obtained by sampling from the backup data based on the set sampling rules. The backup data is the data backup corresponding to the target data. The plurality of second data points and the plurality of first data points correspond one-to-one. Step S6: If the detection information indicates that the plurality of first data points and the plurality of second data points meet the consistency condition, delete the backup data; Step S7: If the detection information indicates that the plurality of first data points and the plurality of second data points do not meet the consistency condition, delete the target data in the designated storage space and store the backup data in the designated storage space; The consistency condition for the plurality of first data points and the plurality of second data points includes: in the plurality of first data points, the data included in each first data point and the data included in the corresponding second data point are the same.

7. A computing resource storage device for an intelligent computing center, characterized in that, The device includes: A data receiving module is used to receive target data, wherein the target data is data to be stored by the user; A data storage module is used to store the target data in a designated storage space, wherein the designated storage space is the data storage space of a storage management system, the storage management system includes multiple storage devices, and the data storage capacity of the designated storage space is at the petabyte level.

8. A server, characterized in that, include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the computing resource storage method for an intelligent computing center as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the intelligent computing center's computing resource storage method 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 of the intelligent computing center's computing resource storage method as described in any one of claims 1 to 6.

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