Method and device for deleting computing power resource garbage for inclusive computing power intelligent computing center

Abstract

This invention provides a method and apparatus for deleting garbage from computing resources in inclusive intelligent computing centers, relating to the field of computing infrastructure technology. The method includes: Step S1, receiving a deletion instruction, the deletion instruction indicating the deletion of data in a target area, the deletion instruction including a deletion timestamp; Step S2, traversing the stored data in the target area, the stored data including at least one version of historical data, each version of historical data corresponding to a timestamp; Step S3, obtaining the operation type corresponding to the stored data, the operation type being the type corresponding to the last operation performed on the stored data; Step S4, deleting at least one historical data included in the stored data based on the deletion timestamp and the operation type. This invention can improve the utilization rate of computing resources in intelligent computing centers, reduce model development costs, and realize the widespread application of inclusive computing power.

Description

Technical Field

[0001] This invention relates to the field of intelligent computing centers, smart computing centers, and computing infrastructure technology, specifically to a method and apparatus for deleting garbage from computing resources in inclusive intelligent computing centers. Background Technology

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

[0003] An "intelligent computing center" refers to a facility that provides the necessary computing power, data, and algorithms for artificial intelligence applications (such as the development, training, and inference of deep learning models) by utilizing large-scale heterogeneous computing resources, including general-purpose and intelligent computing power. Intelligent computing centers encompass facilities, hardware, and software, and can provide full-stack capabilities from underlying computing power to top-level application enablement.

[0004] "Intelligent computing center" includes, but is not limited to, "intelligent computing center".

[0005] "Intelligent computing center" or artificial intelligence computing center is a type of computing infrastructure that provides computing power services, data services, and algorithm services required for artificial intelligence applications, based on artificial intelligence theory and adopting artificial intelligence computing architecture.

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

[0007] Currently, in the process of providing computing power services to users, intelligent computing centers store data within them. During the use of these services, users often modify the data and retain all historical data for model debugging. This large amount of historical data consumes significant resources in the intelligent computing center. Users need to manually delete this unwanted historical data (i.e., computing resource garbage). However, current technology requires users to manually delete unwanted historical data sequentially, which is inefficient and cumbersome, making it difficult to quickly remove computing resource garbage. This results in the long-term occupation of computing center resources and low utilization. Furthermore, the consumption of computing resource garbage necessitates long-term rentals of computing power services by users, leading to higher model development costs and hindering the widespread application of affordable computing power.

[0008] It is evident that existing technologies suffer from low utilization of computing resources and high model development costs. Summary of the Invention

[0009] This invention provides a method and apparatus for deleting garbage from computing resources in inclusive intelligent computing centers, in order to solve the problems of low utilization rate of computing resources and high cost of model development in the prior art.

[0010] To solve the above problems, the present invention is implemented as follows:

[0011] In a first aspect, the present invention provides a method for deleting garbage from computing resources in inclusive intelligent computing centers, comprising:

[0012] Step S1: Receive a deletion instruction, the deletion instruction being used to instruct the deletion of data in the target area, the deletion instruction including a deletion timestamp;

[0013] Step S2: Traverse the stored data of the target area, wherein the stored data includes at least one version of historical data, and each version of historical data corresponds to a timestamp;

[0014] Step S3: Obtain the operation type corresponding to the stored data, wherein the operation type is the type corresponding to the last operation performed on the stored data;

[0015] Step S4: Delete at least one historical data included in the stored data based on the deletion timestamp and the operation type.

[0016] In one embodiment, step S4 includes at least one of the following:

[0017] Step S41: If the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data, delete the historical data in the stored data that is earlier than the deletion timestamp;

[0018] Step S42: If the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data, delete at least one historical data included in the stored data based on the operation type.

[0019] In one embodiment, step S42 includes at least one of the following:

[0020] Step S421: When the operation type is used to characterize adding data, delete historical data other than the latest historical data included in the stored data;

[0021] Step S422: If the operation type is used to characterize deleting data or adding to data to be deleted, deleting the stored data includes all historical data.

[0022] In one embodiment, the stored data of the target region is stored in the form of key-value pairs, the stored data of the target region is arranged sequentially based on the key number in the target region, and at least one historical data included in the stored data is arranged sequentially based on the timestamp order;

[0023] Step S2 includes:

[0024] Step S21: Iterate through at least one historical data included in the stored data of the arranged target area in sequence.

[0025] In one embodiment, the method further includes:

[0026] Step S5: When the cumulative number of historical data traversed reaches a preset number, query whether the intelligent computing center has received a stop instruction. The stop instruction is used to indicate that the deletion of data in the target area should be stopped.

[0027] Step S6: Upon receiving a stop command, the intelligent computing center clears the historical data that has been traversed and stops traversing the data of the target area;

[0028] Step S7: If the intelligent computing center does not receive a stop instruction, clear the accumulated number of historical data traversed, and continue traversing the data of the target area.

[0029] In one embodiment, step S2 includes:

[0030] Step S22: Traverse the stored data of the target area within a preset time period;

[0031] Wherein, the target area is an area corresponding to the target user, the target user is one of multiple users, the multiple users are users who provide computing power services to the intelligent computing center, and the preset time period for traversing the area corresponding to each of the multiple users is different.

[0032] Secondly, the present invention also provides a garbage removal device for computing resources in inclusive intelligent computing centers, comprising:

[0033] A receiving module is used to receive a deletion instruction, the deletion instruction being used to instruct the deletion of data in a target area, the deletion instruction including a deletion timestamp;

[0034] The traversal module is used to traverse the stored data of the target area, the stored data including at least one version of historical data, each version of historical data corresponding to a timestamp;

[0035] The acquisition module is used to acquire the operation type corresponding to the stored data, wherein the operation type is the type corresponding to the last operation performed on the stored data;

[0036] The deletion module is used to delete at least one historical data included in the stored data based on the deletion timestamp and the operation type.

[0037] Thirdly, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the garbage removal method for computing power resources in the inclusive computing power intelligent computing center described in the first aspect above.

[0038] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the garbage removal method for computing power resources in the inclusive computing power intelligent computing center described in the first aspect above.

[0039] Fifthly, the present invention also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps in the method for garbage removal of computing resources in an inclusive intelligent computing center as described in the first aspect above.

[0040] In this invention, a deletion instruction is received, which instructs the deletion of data in a target area. The deletion instruction includes a deletion timestamp. The stored data in the target area is traversed. The stored data includes at least one version of historical data, each version corresponding to a timestamp. The operation type corresponding to the stored data is obtained, where the operation type is the type corresponding to the last operation performed on the stored data. At least one historical data item included in the stored data is deleted based on the deletion timestamp and the operation type. This batch deletion of at least one historical data item included in the stored data is achieved through the deletion timestamp and operation type, improving the efficiency of deleting computing resource garbage, preventing the long-term occupation of computing resources in intelligent computing centers, and improving the utilization rate of computing resources. At the same time, since long-term occupation of computing resources is not required, the cost of model development is reduced, enabling the widespread application of inclusive computing power. Attached Figure Description

[0041] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of a method for deleting garbage from computing resources in an inclusive intelligent computing center, provided by the present invention.

[0043] Figure 2 This is a schematic diagram of the interaction between the user and the intelligent computing center provided by the present invention;

[0044] Figure 3 This is one of the schematic diagrams of modifying stored data provided by the present invention;

[0045] Figure 4 This is one of the schematic diagrams of the stored data of the target area provided by the present invention;

[0046] Figure 5 This is one of the schematic diagrams of deleting historical data provided by the present invention;

[0047] Figure 6 This is the second schematic diagram of deleting historical data provided by the present invention;

[0048] Figure 7 This is the third schematic diagram of deleting historical data provided by the present invention;

[0049] Figure 8 This is the second schematic diagram of modifying stored data provided by the present invention;

[0050] Figure 9 This is the second schematic diagram of the storage data of the target area provided by the present invention;

[0051] Figure 10 This is the fourth schematic diagram of deleting historical data provided by the present invention;

[0052] Figure 11 This is the third schematic diagram of modifying stored data provided by the present invention;

[0053] Figure 12 This is a structural diagram of a garbage removal device for computing power resources in an inclusive intelligent computing center, provided by the present invention.

[0054] Figure 13 This is a structural diagram of an electronic device provided by the present invention. Detailed Implementation

[0055] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0056] The “computing power” mentioned in this invention refers to: the ability of computer equipment or computing / data center to process information; the ability of computer hardware and software to work together to perform a certain computing requirement; the computing power to achieve the target result output by processing information data; and a new type of productivity that integrates information computing power, network carrying capacity, and data storage capacity, mainly providing services to society through computing power infrastructure.

[0057] The "computational power" (CP) described in this invention refers to the ability of a data center server to process data and output results. It is a comprehensive indicator of a data center's computing power, encompassing general computing power, supercomputing power, and intelligent computing power. The commonly used unit of measurement is floating-point operations per second (FLOPS, 1 EFLOPS = 10^18 FLOPS), with higher values ​​indicating stronger overall computing power. It is estimated that 1 EFLOPS is approximately the computing power output of 5 Tianhe-2A supercomputers, 500,000 mainstream server CPUs, or 2 million mainstream laptops. The calculation formula is: CP = CP 通用 +CP 智能 +CP 超级 .

[0058] The "Network Power" (NP) mentioned in this invention refers to the performance of data transmission capability of computing facilities, which includes comprehensive capabilities such as network architecture, network bandwidth, transmission latency, intelligent management and scheduling, and involves network transmission within and between data centers. It is a comprehensive indicator for measuring network transmission scheduling capability.

[0059] The "Storage Power" (SP) described in this invention refers to the comprehensive capabilities of a data center in four aspects: data storage capacity, performance, security and reliability, and green and low-carbon operation. It is a comprehensive indicator for measuring the data storage capacity of a data center, including external storage devices such as storage arrays and internal storage devices within servers. The commonly used unit of measurement for storage capacity is exabytes (EB, 1EB = 2^60 bytes), while the commonly used unit of measurement for performance is the number of read / write operations per second (IOPS / TB). Disaster recovery ratio is an important indicator of security and reliability.

[0060] The "computing infrastructure" mentioned in this invention refers to a new type of information infrastructure that integrates information computing power, network carrying capacity, and data storage capacity. It can realize centralized computing, storage, transmission, and application of information, and exhibits characteristics such as diversity and ubiquity, intelligence and agility, security and reliability, and green and low carbon. It is of great significance for promoting industrial transformation and upgrading, empowering my country's scientific and technological innovation, meeting people's aspirations for a better life, and achieving efficient social governance.

[0061] The "new information infrastructure" described in this invention refers to: network infrastructure such as 5G networks, fiber optic broadband networks, backbone networks, international communication networks, and satellite internet; computing infrastructure such as data centers, general-purpose computing centers, intelligent computing centers, and supercomputing centers; and new technology facilities such as artificial intelligence, blockchain, and quantum computing. With the emergence and widespread application of new general-purpose technologies, the forms of new information infrastructure will become increasingly diverse.

[0062] The “computing power” mentioned in this invention includes: general computing power, intelligent computing power, and supercomputing power.

[0063] The "general computing power" mentioned in this 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.

[0064] The "intelligent computing power" mentioned in this invention refers to: a computing platform deployed on a large scale based on dedicated chips such as GPU (Graphics Processing Unit), FPGA (Field Programmable Gate Array), and ASIC (Application Specific Integrated Circuit) for various artificial intelligence innovative applications, such as natural language processing and machine vision.

[0065] The “supercomputing power” mentioned in this invention refers to the computing power provided by high-performance computing clusters such as supercomputers. It utilizes the centralized computing resources of multiple computer systems working in parallel and uses a dedicated operating system to handle extremely complex or data-intensive problems. It is mainly used for computing in cutting-edge scientific fields, such as planetary simulation, drug molecule design, and gene analysis.

[0066] The "intelligent computing center" described in this invention refers to a facility that, through the use of large-scale heterogeneous computing resources, including general-purpose computing power (CPU) and intelligent computing power (GPU, FPGA, ASIC, etc.), primarily provides the necessary computing power, data, and algorithms for artificial intelligence applications (such as the development, training, and inference of deep learning models). The intelligent computing center encompasses facilities, hardware, and software, and can provide full-stack capabilities from underlying computing power to top-level application enablement.

[0067] The "intelligent computing center" mentioned in this invention includes, but is not limited to, "smart computing center".

[0068] The "intelligent computing center" mentioned in this invention, also known as an artificial intelligence computing center, is a type of computing infrastructure that provides computing power services, data services, and algorithm services required for artificial intelligence applications, based on artificial intelligence theory and adopting an artificial intelligence computing architecture.

[0069] The "computing center" mentioned in this invention refers to a facility that is mainly composed of infrastructure such as wind, thermal, hydro, and electricity, and IT hardware and software equipment, and has computing power, carrying capacity, and storage capacity, including general data centers, intelligent computing centers, supercomputing centers, etc.

[0070] The "supercomputing center" mentioned in this invention refers to a supercomputing data center, which is a data center based on supercomputers or large-scale computing clusters. It can provide large-scale computing, storage and network services and is widely used in aerospace, defense, oil exploration, climate modeling and genome sequencing and other application scenarios.

[0071] The “computing resources” mentioned in this invention refer to the technologies and facilities required for the development of the digital society that have the ability to compute, transmit, store and apply information, 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 guaranteeing resources such as wind, fire, water and electricity.

[0072] The “inclusive computing power” mentioned in this invention refers to providing appropriate and effective computing power services to all social strata and groups with computing power service needs at an affordable cost, based on the requirements of equal opportunity and the principle of commercial sustainability.

[0073] The "model" mentioned in this invention includes, but is not limited to, "large language model" and "multimodal large model".

[0074] The "large language model" mentioned in this invention refers to a large-scale language model (LLM), which is a language model with a large number of parameters. It is designed to understand and generate human language, and is trained with a large amount of text data. It can perform a wide range of tasks, including text summarization, translation, and sentiment analysis.

[0075] The “Multimodal Large Models” mentioned in this invention refer to models that combine multimodal information such as text, images, videos, and audio for training, including but not limited to multimodal large language models.

[0076] The "computing resource garbage" mentioned in this invention refers to redundant data generated during the continuous operation of the computing resources of an intelligent computing center. For example, a large amount of outdated data is generated during the process of generating resource usage information, operation and maintenance information, business information, or other information in the intelligent computing center. To reduce the impact of computing resource garbage on the computing resources of the intelligent computing center, it is necessary to periodically delete outdated data and retain only the data required by users. In this invention, "computing resource garbage" specifically refers to historical data included in the stored data.

[0077] In existing technologies, users need to manually delete unwanted historical data one by one, which is inefficient and cumbersome, making it difficult to quickly delete computing resource junk. This results in the long-term occupation of computing resources in intelligent computing centers, leading to low utilization of computing resources. To improve deletion efficiency, in this invention, users only need to send a deletion timestamp, and the intelligent computing center can automatically delete computing resource junk, thereby reducing the occupation of computing resources in the intelligent computing center and improving the utilization rate of computing resources.

[0078] For details, please see Figure 1 , Figure 1 This is a flowchart of a method for deleting garbage from computing resources in an inclusive intelligent computing center, as provided by the present invention. Figure 1 As shown, it includes the following steps:

[0079] Step S1: Receive a deletion instruction, which is used to instruct the deletion of data in the target area, and the deletion instruction includes a deletion timestamp.

[0080] The above deletion command is a command sent by the user. When the user needs to delete data in the target area, the user sends a deletion command to the intelligent computing center through the terminal. After receiving the deletion command, the intelligent computing center begins to scan the data in the target area and delete it.

[0081] The aforementioned deletion timestamp indicates that the user needs to delete data prior to the timestamp. The timestamp is set by the user. Specifically, when a user needs to delete data in a target area, they can directly select a time point. The terminal generates a deletion command based on this time point, which includes a deletion timestamp indicating the selected time point. This allows users to batch delete data in a target area simply by selecting a time point, improving data deletion efficiency.

[0082] For example, the interaction between the user and the intelligent computing center is as follows: Figure 2 As shown, when data in the intelligent computing center needs to be deleted, the user sends a deletion command, including a deletion timestamp, to the intelligent computing center through a component on the terminal. After receiving the deletion command, the intelligent computing center sends a feedback command to the terminal, which indicates that the intelligent computing center has received the deletion command. Finally, the data in the target area is deleted according to the deletion timestamp.

[0083] The aforementioned target area is the data storage area of ​​the intelligent computing center. This center can provide computing power services to multiple users, with each user corresponding to at least one area for data storage. This segmentation of data across different areas facilitates data management for each user.

[0084] Step S2: Traverse the stored data of the target area. The stored data includes at least one version of historical data, and each version of historical data corresponds to a timestamp.

[0085] It should be noted that users need to adjust the stored data in the target area during debugging, specifically by updating the stored data using commands. After each update, a version of historical data will be added to the stored data, allowing users to easily determine the debugging effect by querying historical data.

[0086] When a user adjusts the stored data in a target area, an adjustment command needs to be sent, which will carry an adjustment timestamp. When the intelligent computing center receives the adjustment command, it adjusts the stored data in the target area and associates the adjusted version with the adjustment timestamp, so as to quickly query different versions of stored data based on time.

[0087] For example, such as Figure 3 As shown, the stored data in the target area includes three data sets, stored as key-value pairs, with historical data being the only type of data. Specifically, the data values ​​were modified at times 1, 2, and 3. At time 1, the value corresponding to key 1 was adjusted to historical data 1, key 2 to historical data 2, and key 3 to historical data 3. At time 2, the value corresponding to key 1 was adjusted to historical data 11, key 2 to historical data 22, and key 3 to historical data 33. At time 3, the value corresponding to key 1 was adjusted to historical data 111, key 2 to historical data 222, and key 3 to historical data 333. In this case, the historical data of the target area includes three versions, each corresponding to a different timestamp.

[0088] In this invention, by traversing the stored data of the target area, the timestamps of the historical data included in the stored data are determined. The timestamps can be used to quickly identify the historical data (i.e., computing resource garbage) that needs to be deleted.

[0089] Step S3: Obtain the operation type corresponding to the stored data, where the operation type is the type corresponding to the last operation performed on the stored data.

[0090] It's important to note that users perform different operations when adjusting stored data, such as adding, deleting, or deleting data upon expiration. Different operations correspond to different operation types. When the last operation differs, deleting data from the target area requires differentiated handling to ensure the model remains stable after deletion and prevent data crashes caused by deleting critical data.

[0091] Step S4: Delete at least one historical data included in the stored data based on the deletion timestamp and the operation type.

[0092] In this invention, a deletion instruction is received, which instructs the deletion of data in a target area. The deletion instruction includes a deletion timestamp. The stored data in the target area is traversed. The stored data includes at least one version of historical data, each version corresponding to a timestamp. The operation type corresponding to the stored data is obtained, where the operation type is the type corresponding to the last operation performed on the stored data. At least one historical data item included in the stored data is deleted based on the deletion timestamp and the operation type. This batch deletion of at least one historical data item included in the stored data is achieved through the deletion timestamp and operation type, improving the efficiency of deleting computing resource garbage, preventing the long-term occupation of computing resources in intelligent computing centers, and improving the utilization rate of computing resources. At the same time, since long-term occupation of computing resources is not required, the cost of model development is reduced, enabling the widespread application of inclusive computing power.

[0093] In some alternative implementations, historical data of the target area can also be deleted directly by deleting the timestamp.

[0094] Specifically, if the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data, then delete the historical data in the stored data that is earlier than the deletion timestamp.

[0095] If the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data, then delete the historical data other than the latest historical data included in the stored data.

[0096] In this invention, historical data in the target area can be deleted directly by deleting the timestamp, which can achieve the deletion of data in the target area more quickly.

[0097] In one embodiment, step S4 includes at least one of the following:

[0098] Step S41: If the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data, delete the historical data in the stored data that is earlier than the deletion timestamp;

[0099] Step S42: If the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data, delete at least one historical data included in the stored data based on the operation type.

[0100] It should be noted that the stored data includes at least one historical data. For some of the stored data, deleting all the historical data will cause the model to crash abnormally; while for the other part of the stored data, the model can still run normally after deleting all the historical data.

[0101] For example, if the deletion timestamp is earlier than the timestamp corresponding to the latest historical data, deleting the historical data earlier than the deletion timestamp will still result in the latest historical data remaining in the stored data, preventing the model from crashing due to the lack of stored data. However, if the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data, deleting the historical data earlier than the deletion timestamp will result in the stored data not including any versions of historical data, potentially leading to the model crashing due to the lack of stored data.

[0102] Furthermore, in cases where all historical data needs to be deleted, it is necessary to determine whether historical data earlier than the deletion timestamp needs to be deleted based on the operation type.

[0103] Specifically, step S42 includes at least one of the following:

[0104] Step S421: When the operation type is used to characterize adding data, delete historical data other than the latest historical data included in the stored data;

[0105] Step S422: If the operation type is used to characterize deleting data or adding to data to be deleted, deleting the stored data includes all historical data.

[0106] The aforementioned data addition includes two scenarios: first, adding a version of historical data when no historical data exists in the stored data; second, modifying the stored data to obtain a new version of historical data when historical data exists in the stored data. It should be noted that when the operation type represents adding data, the latest historical data in the stored data is a crucial parameter for the normal operation of the model. Deleting the latest historical data in the stored data will cause the model to crash; therefore, in this case, the latest historical data must be retained.

[0107] The aforementioned data deletion specifically refers to deleting at least one historical data point from the stored data. It should be noted that when the operation type represents data deletion, the latest historical data in the stored data will not affect the normal operation of the model, and deleting the latest historical data will not cause the model to crash. Therefore, in this case, it is necessary to delete the latest historical data to reduce the consumption of computing resources.

[0108] The aforementioned expired data deletion refers to updating the stored historical data, setting an expiration time, and deleting the latest historical data after the expiration time. It should be noted that when the operation type indicates expired data deletion, the latest historical data can be deleted. Therefore, deleting the latest historical data in the stored data will not cause the model to crash. Thus, in this case, it is necessary to delete the latest historical data to reduce the computational resource consumption of the intelligent computing center.

[0109] In this invention, when the operation type is used to represent adding data, historical data other than the latest historical data is deleted from the stored data; when the operation type is used to represent deleting data or adding data to be deleted, all historical data is deleted from the stored data. Thus, by implementing the deletion of historical data through operation types, the accuracy of deletion is improved, and the computational resources consumed by the intelligent computing center can be further reduced.

[0110] In one embodiment, the stored data of the target region is stored in the form of key-value pairs, the stored data of the target region is arranged sequentially based on the key number in the target region, and at least one historical data included in the stored data is arranged sequentially based on the timestamp order;

[0111] Step S2 includes:

[0112] Step S21: Iterate through at least one historical data included in the stored data of the arranged target area in sequence.

[0113] It should be noted that the stored data includes at least one historical data. In order to facilitate the management of the stored data and historical data in the target area and to enable quick adjustment and deletion, it is necessary to sort the stored data and historical data in the target area.

[0114] For example, such as Figure 4 As shown, the stored data in the target area is arranged sequentially based on key numbers, and the stored data includes at least one historical data item arranged sequentially based on timestamp order. For example, key 1 corresponds to three timestamps: timestamp ts1, timestamp ts2, and timestamp ts3. Timestamp ts1 is earlier than timestamp ts2, and timestamp ts2 is earlier than timestamp ts3. Each timestamp corresponds to one historical data item, i.e., timestamp ts1 corresponds to historical data 1, timestamp ts2 corresponds to historical data 11, and timestamp ts3 corresponds to historical data 111. Based on this, different stored data items are arranged according to their key numbers, i.e., in the order of key 1-key 2-key 3.

[0115] In this invention, the stored data in the target area is stored in key-value pairs. The stored data in the target area is arranged sequentially based on the key number, and at least one historical data included in the stored data is arranged sequentially based on timestamps. This arrangement allows for rapid identification of the latest historical data during data traversal by sequentially iterating through the arranged stored data in the target area, thereby enabling the rapid deletion of historical data.

[0116] For example, such as Figure 5 As shown, when the deletion timestamp is ts1, historical data stored earlier than ts1 needs to be deleted; for example... Figure 6 As shown, when the deletion timestamp is ts2, historical data stored earlier than ts2 needs to be deleted; when the deletion timestamp is ts3, the historical data corresponding to ts3 is the latest historical data, and it is necessary to determine whether to delete it based on the operation type corresponding to the latest historical data.

[0117] Among them, such as Figure 7 As shown, when the operation type corresponding to the latest historical data is "add data," the latest historical data needs to be retained (dashed boxes indicate deletion, solid boxes indicate retention). And as... Figure 8 , Figure 9 , Figure 10 , Figure 11 As shown, if the operation type corresponding to the latest historical data is "delete data" or "delete expired data", all historical data will be deleted.

[0118] In some implementations, code can be written using two variables to achieve data deletion in the target area.

[0119] Specifically, a first variable and a second variable are set. The first variable is used to determine whether there is historical data whose key's timestamp is greater than the deletion timestamp (this can be represented by `bool is_exist_default_key_if_ts_gt_safe_point_ts`). If the first variable is 1, historical data with a timestamp greater than the deletion timestamp exists; if the first variable is 0, historical data with a timestamp greater than the deletion timestamp does not exist. The second variable is used to determine whether the operation type corresponding to the timestamp of the latest historical data is adding data (this can be represented by `bool is_first_put_key_if_ts_le_safe_point_ts`). If the second variable is 1, the operation type is adding data; if the first variable is 0, the operation type is deleting data or deleting data upon expiration.

[0120] During the deletion of data in the target area by the intelligent computing center, if the first variable is 1 and the second variable is 0 or 1, and the timestamp of the latest historical data is later than the deletion timestamp, then the historical data with timestamps later than the deletion timestamp is deleted. If the first variable is 0 and the second variable is 0, and the operation type of the latest historical data is data deletion or data expiration deletion, then the historical data with timestamps later than the deletion timestamp is deleted. If the first variable is 0 and the second variable is 1, and the operation type of the latest historical data is data addition, then it is not deleted, but all other historical data is deleted.

[0121] In one embodiment, the method further includes:

[0122] Step S5: When the cumulative number of historical data traversed reaches a preset number, query whether the intelligent computing center has received a stop instruction. The stop instruction is used to indicate that the deletion of data in the target area should be stopped.

[0123] Step S6: Upon receiving a stop command, the intelligent computing center clears the historical data that has been traversed and stops traversing the data of the target area;

[0124] Step S7: If the intelligent computing center does not receive a stop instruction, clear the accumulated number of historical data traversed, and continue traversing the data of the target area.

[0125] It should be noted that during the process of traversing and deleting data in the target area by the intelligent computing center, other user needs may arise, requiring an interruption of the traversal and deletion of data in the target area, such as the need to back up the data in the target area. In this invention, a stop command is determined after traversing a certain amount of historical data, so as to achieve rapid termination when necessary and avoid the inability to recover data after deletion.

[0126] Specifically, upon receiving a stop command, the intelligent computing center clears all previously traversed historical data and stops traversing the data in the target area. In this way, while traversing the data in the target area, no data is deleted; only historical data that needs to be deleted is identified. Upon receiving the stop command, the previously traversed historical data is cleared, and further deletion is stopped, thus achieving rapid termination of data deletion.

[0127] If the intelligent computing center does not receive a stop command, the accumulated number of historical data traversed is cleared, and the number of historical data traversed is recalculated until the preset number is reached. Only then is it determined whether a stop command has been received. This avoids the intelligent computing center consuming a lot of resources to traverse all the historical data before determining whether to stop, thus reducing the waste of computing resources.

[0128] Furthermore, if the intelligent computing center still does not receive a stop instruction after traversing all historical data, it will delete at least one historical data included in the stored data based on the deletion timestamp and the operation type, thereby deleting the data in the target area.

[0129] In this invention, when the cumulative number of historical data traversed reaches a preset amount, the system queries whether the intelligent computing center has received a stop command. This stop command instructs the deletion of data in the target area to cease. If the intelligent computing center receives the stop command, the traversed historical data is cleared, and traversal of the target area's data stops. If the intelligent computing center does not receive the stop command, the cumulative number of traversed historical data is cleared, and traversal of the target area's data continues. Thus, by determining whether the intelligent computing center has received a stop command based on the cumulative number of traversed historical data, the system achieves this by traversing historical data with minimal resource consumption, reducing waste of computing power.

[0130] In one embodiment, step S2 includes:

[0131] Step S22: Traverse the stored data of the target area within a preset time period;

[0132] Wherein, the target area is an area corresponding to the target user, the target user is one of multiple users, the multiple users are users who provide computing power services to the intelligent computing center, and the preset time period for traversing the area corresponding to each of the multiple users is different.

[0133] It should be noted that the intelligent computing center includes multiple areas to provide computing power services to different users, and the data of different users are not related to each other and need to be isolated.

[0134] In this invention, the target area is a region corresponding to a target user, the target user is one of multiple users, and the multiple users are users who provide computing power services to the intelligent computing center. The preset time period for traversing the region corresponding to each of the multiple users is different. Thus, by traversing the regions corresponding to different users at different time periods, isolation between different users is achieved through time-staggered processing.

[0135] Please see Figure 12 , Figure 12 This is a structural diagram of a garbage removal device for computing power resources in an inclusive intelligent computing center, provided by the present invention. Figure 12 As shown, the computing resource garbage removal device 1200 of the intelligent computing center includes:

[0136] The receiving module 1201 is used to receive a deletion instruction, the deletion instruction being used to instruct the deletion of data in a target area, the deletion instruction including a deletion timestamp;

[0137] The traversal module 1202 is used to traverse the stored data of the target area, the stored data including at least one version of historical data, each version of historical data corresponding to a timestamp;

[0138] The acquisition module 1203 is used to acquire the operation type corresponding to the stored data, wherein the operation type is the type corresponding to the last operation performed on the stored data;

[0139] The deletion module 1204 is used to delete at least one historical data included in the stored data based on the deletion timestamp and the operation type.

[0140] In one embodiment, the deletion module 1204 includes at least one of the following:

[0141] The first deletion unit is used to delete historical data in the stored data that is earlier than the deletion timestamp when the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data.

[0142] The second deletion unit is used to delete at least one historical data included in the stored data based on the operation type when the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data.

[0143] In one embodiment, the second deletion unit includes at least one of the following:

[0144] The first deletion subunit is configured to delete historical data, excluding the latest historical data, from the stored data when the operation type is used to characterize adding data.

[0145] The second deletion subunit is used to delete the stored data, including all historical data, when the operation type is used to characterize deleting data or adding to data to be deleted.

[0146] In one embodiment, the stored data of the target region is stored in the form of key-value pairs, the stored data of the target region is arranged sequentially based on the key number in the target region, and at least one historical data included in the stored data is arranged sequentially based on the timestamp order;

[0147] The traversal module 1202 includes:

[0148] The first traversal unit is used to sequentially traverse at least one historical data included in the stored data of the arranged target area.

[0149] In one embodiment, the garbage removal device 1200 for computing resources in inclusive intelligent computing centers further includes:

[0150] The query module is used to query whether the intelligent computing center has received a stop instruction when the cumulative number of historical data traversed reaches a preset number. The stop instruction is used to instruct the deletion of data in the target area to stop.

[0151] The first processing module is used to clear the historical data that has been traversed and stop traversing the data of the target area when the intelligent computing center receives a stop command;

[0152] The second processing module is used to clear the accumulated number of historical data traversed and continue traversing the data of the target area if the intelligent computing center does not receive a stop instruction.

[0153] In one embodiment, the traversal module 1202 includes:

[0154] The second traversal unit is used to traverse the stored data of the target area within a preset time period;

[0155] Wherein, the target area is an area corresponding to the target user, the target user is one of multiple users, the multiple users are users who provide computing power services to the intelligent computing center, and the preset time period for traversing the area corresponding to each of the multiple users is different.

[0156] The garbage removal device for computing resources in inclusive intelligent computing centers provided by this invention can realize the various processes of the above-mentioned garbage removal method for computing resources in inclusive intelligent computing centers. The technical features are one-to-one and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0157] It should be noted that the garbage removal device for computing power resources in the inclusive computing power intelligent computing center of the present invention can be a device, or it can be a component, integrated circuit or chip in an electronic device.

[0158] The present invention also provides an electronic device, see [link to relevant documentation]. Figure 13 , Figure 13 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device includes a memory 1301, a processor 1302, and a program or instructions stored in the memory 1301 that run on the memory. When the program or instructions are executed by the processor 1302, they can achieve the following: Figure 1 The steps and the same beneficial effects achieved in the corresponding implementation of the garbage removal method for computing power resources in inclusive intelligent computing centers will not be elaborated here.

[0159] The processor 1302 can be a CPU, ASIC, FPGA or GPU.

[0160] Those skilled in the art will understand that all or part of the steps of the above-described embodiments of the method for deleting garbage from computing resources in inclusive intelligent computing centers can be implemented by hardware related to program instructions, and the program can be stored in a readable medium.

[0161] The present invention also provides a readable storage medium on which a computer program is stored, and which, when executed by a processor, can perform the above-described functions. Figure 1 Any step in the corresponding embodiment of the garbage removal method for computing power resources in inclusive intelligent computing centers, which can achieve the same technical effect, will not be described again here to avoid repetition. The storage medium mentioned includes, for example, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0162] The present invention also provides a computer program product, including computer instructions that, when executed by a processor, implement the above-described... Figure 1 The various processes of the corresponding implementation of the garbage removal method for computing power resources in inclusive intelligent computing centers can achieve the same technical effect, and will not be described in detail here to avoid repetition.

[0163] The terms "first," "second," etc., used in this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or apparatuses. Additionally, the use of "and / or" in this application indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: A alone, B alone, C alone, both A and B present, both B and C present, both A and C present, and A, B, and C present.

[0164] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0165] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or second terminal device, etc.) to execute the methods of the various embodiments of this application.

[0166] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for deleting garbage from computing resources in inclusive intelligent computing centers, characterized in that, include: Step S1: Receive a deletion instruction, the deletion instruction being used to instruct the deletion of data in the target area, the deletion instruction including a deletion timestamp; Step S2: Traverse the stored data of the target area, wherein the stored data includes at least one version of historical data, and each version of historical data corresponds to a timestamp; Step S3: Obtain the operation type corresponding to the stored data, wherein the operation type is the type corresponding to the last operation performed on the stored data; Step S4: Delete at least one historical data included in the stored data based on the deletion timestamp and the operation type; Step S4 includes at least one of the following: Step S41: If the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data, delete the historical data in the stored data that is earlier than the deletion timestamp; Step S42: If the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data, delete at least one historical data included in the stored data based on the operation type; Step S42 includes at least one of the following: Step S421: When the operation type is used to characterize adding data, delete historical data other than the latest historical data included in the stored data; Step S422: If the operation type is used to characterize deleting data or adding to data to be deleted, deleting the stored data includes all historical data; The method further includes: Step S5: When the cumulative number of historical data traversed reaches a preset number, query whether the intelligent computing center has received a stop instruction. The stop instruction is used to indicate that the deletion of data in the target area should be stopped. Step S6: Upon receiving a stop command, the intelligent computing center clears the historical data that has been traversed and stops traversing the data of the target area; Step S7: If the intelligent computing center does not receive a stop instruction, clear the accumulated number of historical data traversed, and continue traversing the data of the target area.

2. The method as described in claim 1, characterized in that, The stored data in the target area is stored in the form of key-value pairs. The stored data in the target area is arranged sequentially based on the key number. At least one historical data included in the stored data is arranged sequentially based on the timestamp order. Step S2 includes: Step S21: Iterate through at least one historical data included in the stored data of the arranged target area in sequence.

3. The method as described in claim 1, characterized in that, Step S2 includes: Step S22: Traverse the stored data of the target area within a preset time period; Wherein, the target area is an area corresponding to the target user, the target user is one of multiple users, the multiple users are users who provide computing power services to the intelligent computing center, and the preset time period for traversing the area corresponding to each of the multiple users is different.

4. A device for deleting garbage from computing resources in inclusive intelligent computing centers, characterized in that: include: A receiving module is used to receive a deletion instruction, the deletion instruction being used to instruct the deletion of data in a target area, the deletion instruction including a deletion timestamp; The traversal module is used to traverse the stored data of the target area, the stored data including at least one version of historical data, each version of historical data corresponding to a timestamp; The acquisition module is used to acquire the operation type corresponding to the stored data, wherein the operation type is the type corresponding to the last operation performed on the stored data; The deletion module is used to delete at least one historical data included in the stored data based on the deletion timestamp and the operation type; The deletion module includes at least one of the following: The first deletion unit is used to delete historical data in the stored data that is earlier than the deletion timestamp when the deletion timestamp is earlier than the timestamp corresponding to the latest historical data included in the stored data. The second deletion unit is used to delete at least one historical data included in the stored data based on the operation type when the deletion timestamp is later than or equal to the timestamp corresponding to the latest historical data included in the stored data. The second deletion unit includes at least one of the following: The first deletion subunit is used to delete historical data other than the latest historical data included in the stored data when the operation type is used to characterize adding data. The second deletion subunit is used to delete the stored data, including all historical data, when the operation type is used to characterize data deletion or addition to periodically deleted data. The query module is used to query whether the intelligent computing center has received a stop instruction when the cumulative number of historical data traversed reaches a preset number. The stop instruction is used to instruct the deletion of data in the target area to stop. The first processing module is used to clear the historical data that has been traversed and stop traversing the data of the target area when the intelligent computing center receives a stop command; The second processing module is used to clear the accumulated number of historical data traversed and continue traversing the data of the target area if the intelligent computing center does not receive a stop instruction.

5. An electronic device, 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 garbage removal method for computing power resources in an inclusive intelligent computing center as described in any one of claims 1 to 3.

6. 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 garbage removal method for computing power resources in an inclusive intelligent computing center as described in any one of claims 1 to 3.

7. A computer program product, characterized in that, The method includes computer instructions that, when executed by a processor, implement the steps of the garbage removal method for computing power resources in an inclusive intelligent computing center as described in any one of claims 1 to 3.

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