Information acquisition method and device, electronic equipment and storage medium

Abstract

The disclosure provides an information acquisition method and device, electronic equipment and storage medium, and relates to the fields of artificial intelligence such as machine learning and distributed storage. The method can include: in response to determining that a trigger condition is met, determining a hardware device located on a node to be processed; selecting an XPU from the hardware device; and using a system management interface management tool corresponding to the XPU to acquire predetermined information of the XPU, wherein the predetermined information includes model information of the XPU. The scheme disclosed in the disclosure can save labor and time costs, improve processing efficiency, and ensure the accuracy of processing results.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and in particular to information acquisition methods, devices, electronic devices and storage media in the fields of machine learning and distributed storage. Background Technology

[0002] In machine learning, it is typically necessary to first train a corresponding machine model and then test the model for inference. Both training and inference involve a significant amount of computation, leading to the development of various types of x processors (XPUs) to enhance the computational power of machine learning, such as graphics processing units (GPUs) and tensor processing units (TPUs).

[0003] Currently, most machine learning training and inference tasks are deployed in distributed architecture (Kubernetes) clusters based on container technology. Accordingly, it is necessary to obtain information such as the XPU model on each node in the Kubernetes cluster in order to provide computing power allocation for upper-layer business and ultimately complete the entire machine learning process efficiently. Summary of the Invention

[0004] This disclosure provides information acquisition methods, apparatus, electronic devices, and storage media.

[0005] An information acquisition method, comprising:

[0006] In response to determining that the triggering conditions are met, the hardware device located on the node to be processed is identified;

[0007] Select the x processor (XPU) from the hardware device;

[0008] Using the system management interface tool corresponding to the XPU, the reservation information of the XPU is obtained, including the model information of the XPU.

[0009] An information acquisition device includes: a determining module, a filtering module, and an acquisition module;

[0010] The determining module is used to determine the hardware device located on the node to be processed in response to determining that the triggering condition is met;

[0011] The filtering module is used to filter out the x processor (XPU) from the hardware device;

[0012] The acquisition module is used to acquire the reservation information of the XPU using the system management interface management tool corresponding to the XPU, and the reservation information includes the model information of the XPU.

[0013] An electronic device, comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described above.

[0017] A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the methods described above.

[0018] A computer program product includes a computer program / instructions that, when executed by a processor, implement the method described above.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0020] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0021] Figure 1 This is a flowchart of the first embodiment of the information acquisition method described in this disclosure;

[0022] Figure 2 This is a flowchart of the second embodiment of the information acquisition method described in this disclosure;

[0023] Figure 3 This is a schematic diagram of the composition structure of the first embodiment 300 of the information acquisition device described in this disclosure;

[0024] Figure 4 This is a schematic diagram of the composition structure of the second embodiment 400 of the information acquisition device described in this disclosure;

[0025] Figure 5 A schematic block diagram of an electronic device 500 that can be used to implement embodiments of the present disclosure is shown. Detailed Implementation

[0026] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0027] Furthermore, it should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0028] Figure 1 This is a flowchart of the first embodiment of the information acquisition method described in this disclosure. Figure 1 As shown, the specific implementation methods are as follows.

[0029] In step 101, in response to determining that the triggering condition is met, the hardware device located on the node to be processed is determined.

[0030] In step 102, XPUs are selected from the hardware devices.

[0031] In step 103, the system management interface (SMI) management tool corresponding to the XPU is used to obtain the reservation information of the XPU, which includes the model information of the XPU.

[0032] Traditionally, information such as the model of the XPU on each node in a Kubernetes cluster is obtained manually. When there are many nodes, this requires a lot of manpower and time, is inefficient, and is prone to errors.

[0033] By adopting the solution described in the above method embodiment, information such as the model of the XPU on each node can be automatically obtained, thereby saving manpower and time costs, improving processing efficiency, and ensuring the accuracy of processing results.

[0034] Typically, one XPU is deployed on a single node, but multiple XPUs can be deployed if needed. Whether one or multiple, they can be handled in accordance with the manner described in this disclosure.

[0035] In addition, in practical applications, the execution entity of the above method embodiment can be an x ​​processor detector (XPU-Detector). XPU-Detector is a daemon set type application. Operation and maintenance personnel can pre-deploy an XPU-Detector on each node in the Kubernetes cluster. That is, operation and maintenance personnel can deploy XPU-Detector to the Kubernetes cluster in the Daemon set manner through the Kubernetes package manager (helm). The Daemon set method means that an XPU-Detector is deployed on each node in the cluster.

[0036] Accordingly, each node in the Kubernetes cluster can be used as the node to be processed.

[0037] For a node to be processed, in response to determining that the triggering conditions are met, the hardware device located on the node to be processed can be identified.

[0038] In one embodiment of this disclosure, determining that a trigger condition is met may include: determining that a trigger condition is met in response to determining that a predetermined period of time has elapsed.

[0039] The specific value of the cycle duration can be determined according to actual needs, such as 10 minutes or 1 hour. That is, it can be executed periodically for the node to be processed. Figure 1 The process is shown below.

[0040] In practical applications, the XPUs deployed on nodes may change, such as being changed to different models of XPUs. Through the periodic processing described above, it can be ensured that the information obtained is up-to-date, thereby further improving the accuracy of the information obtained.

[0041] In one embodiment of this disclosure, the hardware devices located on the node to be processed can be obtained by calling the command to display detailed external component interconnect device information (lspci-vv). In other words, all hardware devices on the node to be processed can be queried by calling the lspci-vv command.

[0042] lspci is an abbreviation for "list PCI", where PCI stands for Peripheral Component Interconnect. The hardware devices retrieved can include memory, network interface cards (NICs), central processing units (CPUs), and XPUs, among others.

[0043] As can be seen, the lspci-vv command can efficiently and accurately obtain all the hardware devices on the node to be processed, thus laying a good foundation for subsequent processing.

[0044] After obtaining all the hardware devices on the node to be processed, XPUs can be selected from the hardware devices, and subsequent processing can be performed only on the XPUs in the hardware devices.

[0045] Furthermore, the SMI management tool corresponding to the XPU can be used to obtain the reservation information of the XPU, including the model information of the XPU.

[0046] In one embodiment of this disclosure, the manufacturer identifier of each hardware device can also be obtained by calling the lspci-vv command. That is, by calling the lspci-vv command, each hardware device on the node to be processed and its manufacturer identifier can be obtained simultaneously. Accordingly, the SMI management tool corresponding to the XPU can be obtained based on the XPU's manufacturer identifier.

[0047] By calling the lspci-vv command, you can obtain a piece of data corresponding to each hardware device. This data may include the manufacturer identifier (id) of the corresponding hardware device. The manufacturer identifier is unique and is used to identify different manufacturers.

[0048] In another embodiment of this disclosure, the SMI management tool corresponding to the XPU can be found from a pre-saved list of management tools based on the XPU's vendor identifier. The list of management tools includes different vendor identifiers and their corresponding SMI management tools.

[0049] In other words, XPU-Detector can pre-integrate SMI management tools adapted to various XPU manufacturers. In this way, for the selected XPU, the corresponding SMI management tool can be directly found from the management tool list based on its manufacturer identifier.

[0050] The above processing method can quickly and accurately obtain the required SMI management tools, and it is applicable to XPUs from any manufacturer, meaning it has broad applicability.

[0051] The pre-order information of an XPU can be obtained using the SMI management tool corresponding to the XPU. In one embodiment of this disclosure, the text information corresponding to the XPU can first be obtained using the SMI management tool, which includes the XPU's introductory information. Then, the pre-order information can be extracted from the text information using regular expression matching.

[0052] The text information may include various detailed information about the XPU. Based on the text information, the predetermined information can be extracted from it using regular expression matching. The implementation of regular expression matching is simple and can ensure the accuracy of the extraction results.

[0053] The specific information included in the predetermined information can be determined according to actual needs. For example, in addition to the XPU model information, it may also include the corresponding video memory information of the XPU. The video memory information may include the total amount of video memory, the amount used, and the amount remaining.

[0054] In one embodiment of this disclosure, the predetermined information may also be recorded on the node to be processed.

[0055] For example, the XPU model information and the corresponding video memory information can be recorded on the node to be processed. In addition, other information, such as the XPU manufacturer identification information, can also be recorded.

[0056] Subsequently, the recorded information can be provided to upper-layer business processes for computing power allocation, thereby helping businesses to quickly schedule and deploy to nodes with the appropriate computing power, improving computing power allocation efficiency, and reducing business deployment time.

[0057] Based on the above introduction, Figure 2 This is a flowchart of a second embodiment of the information acquisition method described in this disclosure. Figure 2 As shown, the specific implementation methods are as follows.

[0058] In step 201, in response to determining that the triggering condition is met, the hardware devices located on the node to be processed are obtained by calling the lspci-vv command, and the manufacturer identification information of each hardware device is obtained respectively.

[0059] For example, once a predetermined period of time has elapsed, it can be determined that the triggering condition has been met, and the processing described in this embodiment will be executed.

[0060] In step 202, XPUs are selected from the hardware devices.

[0061] Suppose that only one XPU is selected.

[0062] In step 203, based on the vendor identifier of the XPU, the SMI management tool corresponding to the XPU is retrieved from a pre-saved list of management tools. The list of management tools includes different vendor identifiers and their corresponding SMI management tools.

[0063] You can then obtain the corresponding SMI management tool for the XPU based on its manufacturer identification information.

[0064] In step 204, the SMI management tool corresponding to the XPU is used to obtain the text information corresponding to the XPU, which includes the introductory information of the XPU.

[0065] In step 205, the predetermined information of the XPU is extracted from the text information by regular expression matching. The predetermined information includes the model information of the XPU.

[0066] The predetermined information may also include the video memory information corresponding to the XPU, and there is no limitation on what information is included.

[0067] In step 206, the predetermined information is recorded on the node to be processed.

[0068] For example, the model information of the XPU and the corresponding video memory information of the XPU can be recorded on the node to be processed. In addition, some other information can be recorded, such as the manufacturer identification information of the XPU.

[0069] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this disclosure. Secondly, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this disclosure. Furthermore, for parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0070] In summary, by adopting the scheme described in the embodiments of this disclosure, information such as the XPU model on each node can be automatically obtained, thereby saving manpower and time costs, improving processing efficiency and ensuring the accuracy of processing results. Moreover, it can help upper-layer services to quickly schedule and deploy to nodes with corresponding computing power, improve computing power allocation efficiency, and reduce service deployment time.

[0071] The above is an introduction to the method embodiments. The following describes the solution described in this disclosure further through device embodiments.

[0072] Figure 3 This is a schematic diagram of the structural composition of the first embodiment 300 of the information acquisition device described in this disclosure. Figure 3 As shown, it includes: a determination module 301, a filtering module 302, and an acquisition module 303.

[0073] The determination module 301 is used to determine the hardware device located on the node to be processed in response to determining that the triggering condition is met.

[0074] The screening module 302 is used to screen out XPUs from the hardware device.

[0075] The acquisition module 303 is used to acquire the reservation information of the XPU using the SMI management tool corresponding to the XPU, wherein the reservation information includes the model information of the XPU.

[0076] By adopting the solution described in the above device embodiment, information such as the model of the XPU on each node can be automatically obtained, thereby saving manpower and time costs, improving processing efficiency, and ensuring the accuracy of processing results.

[0077] In practical applications, each node in the Kubernetes cluster can be used as the node to be processed.

[0078] For a node to be processed, the determination module 301 can determine the hardware device located on the node to be processed in response to determining that the triggering conditions are met.

[0079] In one embodiment of this disclosure, determining that the trigger condition is met may include: determining that the trigger condition is met in response to determining that a predetermined period of time has elapsed. The specific value of the period of time may be determined according to actual needs, such as 10 minutes or 1 hour.

[0080] In one embodiment of this disclosure, the determining module 301 can obtain the hardware devices located on the node to be processed by calling the lspci-vv command, that is, all hardware devices on the node to be processed can be queried by calling the lspci-vv command.

[0081] The hardware devices that can be found include memory, network cards, CPUs, and XPUs.

[0082] After acquiring all the hardware devices on the node to be processed, the filtering module 302 can filter out the XPUs from the hardware devices, so that subsequent processing can be performed only on the XPUs in the hardware devices.

[0083] Furthermore, the acquisition module 303 can use the SMI management tool corresponding to the XPU to obtain the reservation information of the XPU, which includes the model information of the XPU.

[0084] In one embodiment of this disclosure, the determining module 301 can also obtain the manufacturer identification information of each hardware device by calling the lspci-vv command. That is, by calling the lspci-vv command, the manufacturer identification information of each hardware device on the node to be processed can be obtained at the same time. Accordingly, the obtaining module 303 can obtain the SMI management tool corresponding to the XPU based on the manufacturer identification information of the XPU.

[0085] By calling the lspci-vv command, a single data entry can be obtained for each hardware device. This entry may include the manufacturer identification information of the corresponding hardware device. The manufacturer identification is unique and is used to identify different manufacturers.

[0086] In another embodiment of this disclosure, the acquisition module 303 can find the SMI management tool corresponding to the XPU from a pre-saved management tool list based on the XPU's manufacturer identifier. The management tool list includes different manufacturer identifiers and their corresponding SMI management tools.

[0087] In other words, the management tool list can be pre-integrated with SMI management tools adapted to each XPU vendor. In this way, for the selected XPU, the corresponding SMI management tool can be directly found from the management tool list based on its vendor identifier.

[0088] Using the SMI management tool corresponding to the XPU, the pre-defined information of the XPU can be obtained. In one embodiment of this disclosure, the acquisition module 303 can first use the SMI management tool corresponding to the XPU to obtain the text information corresponding to the XPU, the text information including the XPU's introductory information, and then extract the pre-defined information from the text information using regular expression matching.

[0089] The specific information included in the predetermined information can be determined according to actual needs. For example, in addition to the XPU model information, it may also include the corresponding video memory information of the XPU. The video memory information may include the total amount of video memory, the amount used, and the amount remaining.

[0090] Figure 4 This is a schematic diagram of the structural composition of the second embodiment 400 of the information acquisition device described in this disclosure. Figure 4 As shown, it includes: a determination module 301, a filtering module 302, an acquisition module 303, and a recording module 304.

[0091] Among them, the determining module 301, the filtering module 302, and the obtaining module 303 are... Figure 3 The same applies to the embodiments shown.

[0092] The recording module 304 is used to record the acquired predetermined information onto the node to be processed.

[0093] For example, the XPU model information and the corresponding video memory information can be recorded on the node to be processed. In addition, other information, such as the XPU manufacturer identification information, can also be recorded.

[0094] Figure 3 and Figure 4 The specific workflow of the device embodiment shown can be found in the relevant descriptions in the foregoing method embodiments, and will not be repeated here.

[0095] In summary, by adopting the solution described in the embodiments of this disclosure, information such as the XPU model on each node can be automatically obtained, thereby saving manpower and time costs, improving processing efficiency and ensuring the accuracy of processing results. Moreover, it can help upper-layer services to be quickly scheduled and deployed to nodes with corresponding computing power, improving computing power allocation efficiency and reducing service deployment time.

[0096] The solutions described in this disclosure can be applied to the field of artificial intelligence, particularly machine learning and distributed storage. Artificial intelligence is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It involves both hardware and software technologies. Artificial intelligence hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. Artificial intelligence software technologies mainly include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0097] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0098] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0099] Figure 5 A schematic block diagram of an electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0100] like Figure 5As shown, device 500 includes a computing unit 501, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 502 or a computer program loaded from storage unit 508 into random access memory (RAM) 503. RAM 503 may also store various programs and data required for the operation of device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0101] Multiple components in device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0102] The computing unit 501 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as those described in this disclosure. For example, in some embodiments, the methods described in this disclosure can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the methods described in this disclosure can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the methods described in this disclosure by any other suitable means (e.g., by means of firmware).

[0103] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0104] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0105] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0106] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0107] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0108] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0109] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0110] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An information acquisition method, wherein the execution entity of the method is an x ​​processor detector deployed on nodes of a container-based distributed architecture cluster, comprising: In response to the determination that the triggering conditions are met, the system obtains the hardware devices and their manufacturer identifiers on the node to be processed by calling a command to display detailed information on external component interconnect devices. Select the x processor (XPU) from the hardware device; Based on the manufacturer identifier of the XPU, the system management interface (SMI) management tool corresponding to the XPU is retrieved from a pre-saved list of management tools. The list of management tools includes different manufacturer identifiers and their corresponding SMI management tools. Using the SMI management tool corresponding to the XPU, the text information corresponding to the XPU is obtained. The text information includes the introduction information of the XPU. The pre-determined information, including the model information of the XPU, is extracted from the text information.

2. The method according to claim 1, wherein, The extraction of predetermined information from the text information includes: The predetermined information is extracted from the text information using regular expression matching.

3. The method according to any one of claims 1 to 2, further comprising: The predetermined information is recorded on the node to be processed.

4. The method according to any one of claims 1 to 2, wherein, The determination that the trigger condition is met includes: in response to determining that a predetermined period of time has elapsed, determining that the trigger condition is met.

5. An information acquisition device, said device being an x ​​processor detector deployed on nodes of a container-based distributed architecture cluster, comprising: Identify modules, filter modules, and obtain modules; The determining module is used to obtain each hardware device and its manufacturer identifier on the node to be processed by calling a command to display detailed external component interconnection device information in response to determining that the triggering condition is met. The filtering module is used to filter out the x processor (XPU) from the hardware device; The acquisition module is used to find the corresponding System Management Interface (SMI) management tool for the XPU from a pre-saved list of management tools based on the manufacturer identifier of the XPU. The list of management tools includes different manufacturer identifiers and their corresponding SMI management tools. Using the SMI management tool corresponding to the XPU, the module acquires the corresponding text information of the XPU, which includes the introduction information of the XPU. The module also extracts pre-defined information from the text information, which includes the model information of the XPU.

6. The apparatus according to claim 5, wherein, The acquisition module extracts the predetermined information from the text information using regular expression matching.

7. The apparatus according to any one of claims 5 to 6, further comprising: A recording module is used to record the predetermined information onto the node to be processed.

8. The apparatus according to any one of claims 5 to 6, wherein, The determining module determines that the triggering condition is met upon determining that a predetermined period of time has elapsed.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

11. A computer program product comprising a computer program / instructions that, when executed by a processor, implement the method of any one of claims 1-4.

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