Device optimization method and apparatus, computer device, and storage medium

Abstract

This application relates to a device optimization method, apparatus, computer equipment, and storage medium, belonging to the field of computing power equipment technology. The method includes: determining the hardware performance test results of target hardware; determining a first optimization strategy based on computing power service requirements and hardware performance test results; and optimizing the edge computing device based on the first optimization strategy. The target hardware is the hardware within the edge computing device. In this application, the first optimization strategy is determined by determining the obtained hardware performance test results of the target hardware and the computing power service requirements. That is, when determining the first optimization strategy, not only the hardware performance test results but also the computing power service requirements are considered. This ensures that after optimizing the edge computing device based on the first optimization strategy, the hardware performance can be fully utilized, effectively solving the problem of domestically produced hardware being difficult to adapt to edge computing devices, while simultaneously improving the real-time performance and stability of the edge computing device.

Description

Technical Field

[0001] This application relates to the field of computing power equipment technology, and in particular to a method, apparatus, computer equipment, and storage medium for optimizing equipment. Background Technology

[0002] With the rapid development of technologies such as the Internet of Things (IoT) and the Industrial Internet, edge computing, as a new computing model that brings computing and data storage closer to the data source, is gradually becoming a focus of industry attention. Edge computing enables real-time data processing and analysis locally, reducing data transmission latency, improving system response speed, and simultaneously reducing cloud data processing pressure and network bandwidth requirements.

[0003] In recent years, domestically produced hardware has made significant progress in performance, reliability, and security, gradually becoming an important choice for edge computing devices. However, there are still significant differences between domestically produced hardware and mainstream international hardware in terms of architecture design, instruction sets, and peripheral interfaces. This results in edge computing devices based on domestically produced hardware having poor real-time performance and reliability when processing data, making it difficult to meet users' computing power needs. Summary of the Invention

[0004] Therefore, it is necessary to provide a device optimization method, apparatus, computer equipment, and storage medium to improve the real-time performance and stability of edge computing devices in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for optimizing equipment. The method includes:

[0006] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0007] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0008] Based on the first optimization strategy, edge computing devices are optimized.

[0009] In one embodiment, determining the hardware performance test results of the target hardware includes:

[0010] The target hardware is subjected to performance tests on the target indicators to obtain the hardware performance test results; the hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0011] In one embodiment, a first optimization strategy is determined based on computing power service requirements and hardware performance test results, including:

[0012] Based on computing power service requirements and hardware performance test results, determine the peak hardware performance information of the target hardware;

[0013] The hardware performance evaluation results are determined based on the hardware performance test results and hardware performance peak information.

[0014] Based on the hardware performance evaluation results, a first optimization strategy is determined; wherein the first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0015] In one embodiment, the edge computing device is optimized based on a first optimization strategy, including:

[0016] The performance of the edge computing device is optimized based on the first optimization strategy to obtain the first edge device;

[0017] During the operation of the first edge device, acquire the hardware operation information of the target hardware;

[0018] Based on hardware operation information, a second optimization strategy is determined;

[0019] The first edge device is optimized based on the second optimization strategy.

[0020] In one embodiment, a second optimization strategy is determined based on hardware operating information, including:

[0021] Based on hardware operation information, the service processing status of the first edge device is determined; the hardware operation information includes processor temperature information, device load information, and memory usage information.

[0022] Determine the resource allocation strategy based on the business processing status;

[0023] Based on the resource allocation strategy, a second optimization strategy is determined.

[0024] In one embodiment, determining a second optimization strategy based on a resource allocation strategy includes:

[0025] Based on the business processing status, determine the business processing strategy; the business processing strategy includes the business priority allocation strategy, processing thread allocation strategy and transmission strategy for different business types;

[0026] We will use business processing strategies and resource allocation strategies as the second optimization strategies.

[0027] In one embodiment, after optimizing the first edge device based on the second optimization strategy, the method further includes:

[0028] Obtain optimized device operation information for the first edge device; the device operation information includes data processing time, data processing accuracy, and system failure rate.

[0029] Based on the equipment operation information, the optimization result of the first edge device is determined.

[0030] Secondly, this application also provides an equipment optimization apparatus, which includes:

[0031] The first determining module is used to determine the hardware performance test results of the target hardware; wherein, the target hardware is the hardware in the edge computing device;

[0032] The second determining module is used to determine the first optimization strategy based on computing power service requirements and hardware performance test results;

[0033] The optimization module is used to optimize edge computing devices based on the first optimization strategy.

[0034] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0035] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0036] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0037] Based on the first optimization strategy, edge computing devices are optimized.

[0038] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0039] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0040] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0041] Based on the first optimization strategy, edge computing devices are optimized.

[0042] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0043] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0044] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0045] Based on the first optimization strategy, edge computing devices are optimized.

[0046] The aforementioned equipment optimization method, apparatus, computer equipment, and storage medium determine the hardware performance test results of the target hardware. Based on computing power service requirements and the hardware performance test results, a first optimization strategy is determined. Based on the first optimization strategy, the edge computing device is optimized. Here, the target hardware refers to the hardware within the edge computing device. In this application, the first optimization strategy is determined by identifying the obtained hardware performance test results of the target hardware and the computing power service requirements. That is, when determining the first optimization strategy, not only the hardware performance test results but also the computing power service requirements are considered. This ensures that after optimizing the edge computing device based on the first optimization strategy, the hardware performance can be fully utilized, effectively solving the problem of domestically produced hardware being difficult to adapt to edge computing devices, while simultaneously improving the real-time performance and stability of the edge computing device. Attached Figure Description

[0047] Figure 1 This is a diagram illustrating the application environment of the device optimization method provided in this embodiment.

[0048] Figure 2 This is a flowchart illustrating the first equipment optimization method provided in this embodiment;

[0049] Figure 3 This is a flowchart illustrating the process of determining the first optimization strategy provided in this embodiment;

[0050] Figure 4 This is a schematic diagram of the process for optimizing the first edge device provided in this embodiment;

[0051] Figure 5 This is a flowchart illustrating the second equipment optimization method provided in this embodiment;

[0052] Figure 6 This is a structural block diagram of an equipment optimization device provided in this embodiment;

[0053] Figure 7 This is an internal structural diagram of the computer device provided in this embodiment. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0055] With the rapid development of technologies such as the Internet of Things (IoT) and the Industrial Internet, edge computing, as a new computing model that brings computing and data storage closer to the data source, is gradually becoming a focus of industry attention. Edge computing enables real-time data processing and analysis locally, reducing data transmission latency, improving system response speed, and simultaneously reducing cloud data processing pressure and network bandwidth requirements.

[0056] In recent years, domestically produced hardware has made significant progress in performance, reliability, and security, gradually becoming an important choice for edge computing devices. However, there are still significant differences between domestically produced hardware and mainstream international hardware in terms of architecture design, instruction sets, and peripheral interfaces. This results in edge computing devices based on domestically produced hardware having poor real-time performance and reliability when processing data, making it difficult to meet users' computing power needs.

[0057] To address the aforementioned challenges, the device optimization method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, server 104 determines the hardware performance test results of the target hardware. Based on the computing power service requirements and the hardware performance test results, server 104 determines a first optimization strategy. Based on the first optimization strategy, server 104 optimizes the edge computing device 102. The target hardware is the hardware within the edge computing device 102.

[0058] The server can be a standalone server or a server cluster. Edge computing devices refer to devices capable of providing computing power or services at the edge. Edge computing is a new computing model that brings computing and data storage closer to the data source, and it is gradually becoming a focus of industry attention. Edge computing can process and analyze data locally in real time, reducing data transmission latency, improving system response speed, and reducing cloud data processing pressure and network bandwidth requirements.

[0059] In one embodiment, such as Figure 2 As shown, a device optimization method is provided, which is applied to Figure 1 Taking the server in the example, the following steps are included:

[0060] S201, Determine the hardware performance test results of the target hardware.

[0061] The target hardware refers to the hardware within an edge computing device. An edge computing device is a device that inherits the target hardware (e.g., domestically produced hardware) and provides edge computing services. Edge computing devices are computing devices deployed close to the data source (such as industrial equipment, IoT terminals, user terminals, etc.), possessing local data collection, processing, storage, and basic analysis capabilities. They can reduce latency and bandwidth consumption during data transmission to the cloud and are often suited to the real-time and low-power requirements of edge scenarios (e.g., domestically produced edge servers, edge gateways, embedded edge computing modules, etc.). The target hardware can be computing chips, processors, memory, or components integrating multiple hardware components (e.g., computing boards).

[0062] As an optional implementation of this application, performance testing is performed on the target hardware to obtain hardware performance test results. The hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate. Specifically, performance testing is performed on the target hardware based on hardware performance testing tools to obtain hardware performance test results.

[0063] Another optional implementation of this application embodiment is to send a query request to the query device, wherein the query request carries a hardware identifier (e.g., model number) of the target hardware, so that the query device queries the hardware performance test results of the target hardware based on the hardware identifier and sends the hardware performance test results of the target hardware to the server.

[0064] S202, based on computing power service requirements and hardware performance test results, determines the first optimization strategy.

[0065] The first optimization strategy refers to an optimization strategy used to optimize edge computing devices. Computing power service requirements refer to the amount of computing power required by edge computing devices in an edge computing scenario (e.g., data processing volume), as well as the corresponding requirements for computing power services (e.g., time requirements, response speed requirements, computing power precision and accuracy requirements).

[0066] As an optional implementation of this application, the computing power service requirements and hardware performance test results are input into the strategy generation model, and the strategy generation model outputs a first optimization strategy based on the computing power service requirements and hardware performance test results.

[0067] Another optional implementation method according to this application is to comprehensively analyze the computing power service requirements and hardware performance test results to obtain hardware defect information of the target hardware. Based on the hardware defect information, a first optimization strategy is determined.

[0068] S203 optimizes edge computing devices based on the first optimization strategy.

[0069] Optionally, in this embodiment, based on the first optimization strategy, the optimization direction and optimization measures are determined, and the edge computing device is optimized based on the optimization direction and optimization measures.

[0070] The aforementioned device optimization method determines the hardware performance test results of the target hardware. Based on the computing power service requirements and the hardware performance test results, a first optimization strategy is determined. The edge computing device is then optimized based on the first optimization strategy. Here, the target hardware refers to the hardware within the edge computing device. In this application, the first optimization strategy is determined by identifying the obtained hardware performance test results of the target hardware and the computing power service requirements. That is, when determining the first optimization strategy, not only the hardware performance test results but also the computing power service requirements are considered. This ensures that after optimizing the edge computing device based on the first optimization strategy, the hardware performance can be fully utilized, effectively solving the problem of domestically produced hardware being difficult to adapt to edge computing devices, while simultaneously improving the real-time performance and stability of the edge computing device.

[0071] In one embodiment, to more accurately determine the first optimization strategy, such as Figure 3 As shown, based on computing power service requirements and hardware performance test results, another optional implementation method for the first optimization strategy is determined, including:

[0072] S301 determines the peak hardware performance information of the target hardware based on computing power service requirements and hardware performance test results.

[0073] Among them, peak hardware performance information refers to hardware performance bottleneck information.

[0074] Optionally, in this embodiment, based on the processor's computing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, network interface transmission rate, and computing power service requirements from the hardware performance test results, a comprehensive analysis is conducted on the target hardware's peak hardware information when processing computing power service requirements (which include data processing volume and requirement information such as time requirements, response speed requirements, computing power precision and accuracy requirements). For example, the processor may have insufficient computing power when processing complex algorithms, or the storage device may experience excessive latency during high-concurrency data read / write operations.

[0075] S302 determines the hardware performance evaluation result based on hardware performance test results and hardware performance peak information.

[0076] As an optional implementation of this application, the hardware performance test results and hardware performance peak information are used as the hardware performance evaluation results.

[0077] Another optional implementation of this application involves comprehensively evaluating the hardware performance test results and peak hardware performance information to determine the target hardware's performance information and peak performance information for the target metric. The target hardware's performance information and peak performance information for the target metric are then used as the hardware performance evaluation result.

[0078] S303 determines the first optimization strategy based on the hardware performance evaluation results.

[0079] The first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0080] Optionally, in this embodiment, based on the hardware performance evaluation results, optimization metrics for the target hardware and corresponding optimization measures are determined. Based on the optimization metrics and corresponding optimization measures, corresponding optimization strategies (e.g., algorithm optimization strategies, code optimization strategies, and cache optimization strategies) are determined. Here, optimization metrics refer to metrics that need to be optimized, such as processor computation metrics, memory read metrics, etc.

[0081] In this embodiment, the peak hardware performance information of the target hardware is determined based on the computing power service requirements and hardware performance test results. Based on the hardware performance test results and the peak hardware performance information, a hardware performance evaluation result is determined. Based on the hardware performance evaluation result, a first optimization strategy is determined; the first optimization strategy includes at least one of an algorithm optimization strategy, a code optimization strategy, and a cache optimization strategy. This embodiment makes the determined first optimization strategy more effective, further improving the adaptability and efficiency between the target hardware and edge computing devices.

[0082] In one embodiment, in order to comprehensively optimize edge computing devices and further improve the adaptability of domestically produced hardware in edge computing devices, such as Figure 4 As shown, an optional implementation method for optimizing edge computing devices based on the first optimization strategy includes:

[0083] S401, Based on the first optimization strategy, the performance of the edge computing device is optimized to obtain the first edge device.

[0084] The first edge device refers to the optimized edge computing device.

[0085] Optionally, in this embodiment, the edge computing device is optimized based on the optimization indicators and corresponding optimization strategies in the first optimization strategy to obtain the first edge device. For example, if the optimization indicator is a processor performance indicator, and the optimization strategy is an algorithm optimization strategy, for instance, to improve the processor performance indicator and enable the processor performance to exceed the peak performance obtained from testing, the algorithm optimization strategy is to optimize and simplify the algorithms in the software, adopting efficient algorithms suitable for domestic hardware architectures. For example, some complex floating-point operations are converted into fixed-point operations more suitable for domestic processors, reducing the processor's computational complexity. For example, if the optimization indicator is a memory and storage performance indicator, the optimization measure is a memory optimization strategy. Based on the memory optimization strategy, data storage and retrieval strategies are optimized, and a caching mechanism is adopted to store frequently accessed data in a high-speed cache, reducing the number of accesses to low-speed storage devices. For example, if the optimization indicator is code execution efficiency, the optimization strategy can be a code optimization strategy. Based on the code optimization strategy, according to the instruction set characteristics of domestic hardware, the software code is recompiled and optimized to improve code execution efficiency.

[0086] S402: During the operation of the first edge device, acquire the hardware operation information of the target hardware.

[0087] Optionally, the hardware operating information in this embodiment includes, but is not limited to, processor temperature information, device load information, and memory usage information.

[0088] Optionally, in this embodiment, the hardware operation information of the target hardware is obtained based on a hardware monitoring module. Specifically, a dedicated hardware monitoring module is additionally developed or integrated into the edge computing device. This module acts like a "monitor," capable of establishing an information interaction channel with the target hardware. It actively acquires the hardware operation information of the target hardware according to set rules and frequencies, thereby achieving real-time monitoring of the target hardware's operating status.

[0089] S403 determines the second optimization strategy based on hardware operation information.

[0090] Optionally, in this embodiment, the service processing status of the first edge device is determined based on hardware operation information. A resource allocation strategy is determined based on the service processing status. A second optimization strategy is then determined based on the resource allocation strategy.

[0091] In this embodiment, an optional implementation for determining the service processing status of the first edge device based on hardware operation information is to determine the service processing status of the first edge device based on various indicator information in the hardware operation information. For example, if the processor temperature is too high (e.g., exceeding a preset threshold), the service processing status is determined to be a decline in service processing performance and a risk of hardware damage. For example, the level of service processing busyness can be determined based on device load. For example, based on memory usage (including used memory, remaining memory, etc.), it can be determined whether there is a risk of insufficient memory causing program lag, which in turn leads to service processing lag or delay. For example, based on the read / write speed and frequency of the storage device, it can be determined whether the service storage performance meets the data processing requirements. Based on network interface traffic and connection status, it can be determined whether service data transmission is smooth and whether there are network failures.

[0092] In this embodiment, based on the business processing status, the optional implementation of the resource allocation strategy is as follows: when the business processing status is excessively busy, i.e., the business load is too high, the resource allocation strategy is for the software to automatically delay some non-critical tasks or allocate them to other idle hardware resources, thereby achieving rational utilization of hardware resources. Simultaneously, hardware manufacturers, based on software feedback regarding hardware requirements, make targeted improvements and optimizations to the hardware, such as adjusting the processor clock frequency and optimizing the memory controller design, to achieve deep collaboration between hardware and software.

[0093] In this embodiment, the optional implementation of the second optimization strategy based on the resource allocation strategy is as follows: The business processing strategy is determined according to the business processing status. This business processing strategy includes a business priority allocation strategy for different business types, a processing thread allocation strategy, and a transmission strategy. The business processing strategy and the resource allocation strategy are used as the second optimization strategy. In this embodiment, the optional way to determine the business processing strategy based on the business processing status is as follows: When the business processing status is characterized by decreased business processing performance, a processing thread allocation strategy can be implemented. For example, tasks such as data acquisition, processing, and transmission can be allocated to different threads for parallel execution, reducing the processing time for various types of data. Important business tasks can be allocated to independent threads to improve the processing time of such tasks, thereby improving processor performance. When the business processing status is characterized by business processing lag, the business processing strategy is determined to be a business priority allocation strategy for different business types. For example, a data priority queue is set up in the software, and data is prioritized according to its importance and real-time requirements. Data with high real-time requirements is processed and transmitted first.

[0094] S404, based on the second optimization strategy, optimizes the first edge device.

[0095] Optionally, in this embodiment, the first edge device is optimized based on resource allocation and service processing strategies. That is, the resource allocation and service processing strategies are executed simultaneously, enabling comprehensive optimization and ensuring the stability and timeliness of the edge computing device during service processing.

[0096] Optionally, in this embodiment, after optimizing the first edge device based on the second optimization strategy, one possible implementation of the device optimization method is to obtain the device operation information of the optimized first edge device; wherein, the device operation information includes data processing time, data processing accuracy, and system failure rate. Based on the device operation information, the optimization result of the optimized first edge device is determined. Specifically, in a simulated scenario, sample business data of different types and scales are input to test the data processing capability, real-time performance, and stability of the optimized first edge device. Various device operation information during the testing process is collected, such as data processing time, accuracy, and system failure rate. Based on the device operation information, the adaptation method is optimized and iterated. If the data processing speed does not meet expectations, the software algorithm is further optimized or the hardware-software collaboration strategy is adjusted; if system stability issues occur, the software code is debugged and optimized, potential hardware failures are investigated, and the performance and reliability of the optimized first edge device are continuously improved.

[0097] In this embodiment, the performance of the edge computing device is optimized based on a first optimization strategy to obtain a first edge device. During the operation of the first edge device, hardware operation information of the target hardware is acquired. Based on the hardware operation information, a second optimization strategy is determined. Based on the second optimization strategy, the first edge device is optimized. In this embodiment, the edge computing device is comprehensively optimized through the first and second optimization strategies, improving the compatibility between the target hardware and the edge computing device, thereby improving the response speed, stability, and accuracy of the edge computing device.

[0098] In one embodiment, such as Figure 5 As shown, another optional implementation of a device optimization method is as follows:

[0099] S501 performs performance tests on the target hardware to obtain hardware performance test results. These results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0100] S502 determines the peak hardware performance information of the target hardware based on computing power service requirements and hardware performance test results.

[0101] S503 determines the hardware performance evaluation result based on hardware performance test results and hardware performance peak information.

[0102] S504, based on the hardware performance evaluation results, determines a first optimization strategy. The first optimization strategy includes at least one of an algorithm optimization strategy, a code optimization strategy, and a cache optimization strategy.

[0103] S505, based on the first optimization strategy, optimizes the performance of the edge computing device to obtain the first edge device.

[0104] S506: During the operation of the first edge device, acquire the hardware operation information of the target hardware.

[0105] S507 determines the service processing status of the first edge device based on hardware operation information. This hardware operation information includes processor temperature information, device load information, and memory usage information.

[0106] S508 determines the resource allocation strategy based on the business processing status.

[0107] S509 determines the business processing strategy based on the business processing status. This strategy includes a business priority allocation strategy, a processing thread allocation strategy, and a transmission strategy for different business types.

[0108] S510 uses business processing strategy and resource allocation strategy as the second optimization strategy.

[0109] S511 optimizes the first edge device based on the second optimization strategy.

[0110] S512: Obtain the optimized device operation information of the first edge device. This device operation information includes data processing time, data processing accuracy, and system failure rate.

[0111] S513 determines the optimization result of the first edge device based on the device operation information.

[0112] In this embodiment, the hardware performance test results of the target hardware are determined. Based on the computing power service requirements and the hardware performance test results, a first optimization strategy is determined. Based on the first optimization strategy, the edge computing device is optimized. The target hardware refers to the hardware within the edge computing device. In this application, the first optimization strategy is determined by identifying the obtained hardware performance test results of the target hardware and the computing power service requirements. That is, when determining the first optimization strategy, not only the hardware performance test results but also the computing power service requirements are considered. This ensures that after optimizing the edge computing device based on the first optimization strategy, the hardware performance can be fully utilized, effectively solving the problem of domestically produced hardware being difficult to adapt to edge computing devices, while simultaneously improving the real-time performance and stability of the edge computing device.

[0113] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0114] Based on the same inventive concept, this application also provides a device optimization apparatus for implementing the device optimization method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more device optimization apparatus embodiments provided below can be found in the limitations of the device optimization method described above, and will not be repeated here.

[0115] In one embodiment, such as Figure 6 As shown, a device optimization apparatus 1 is provided, comprising: a first determining module 10, a second determining module 20, and an optimization module 30, wherein:

[0116] The first determining module 10 is used to determine the hardware performance test results of the target hardware; wherein, the target hardware is the hardware in the edge computing device;

[0117] The second determining module 20 is used to determine the first optimization strategy based on computing power service requirements and hardware performance test results;

[0118] The optimization module 30 is used to optimize the edge computing device based on the first optimization strategy.

[0119] The device optimization apparatus in this embodiment determines the hardware performance test results of the target hardware. Based on the computing power service requirements and the hardware performance test results, a first optimization strategy is determined. The edge computing device is then optimized based on the first optimization strategy. Here, the target hardware is the hardware within the edge computing device. In this application, the first optimization strategy is determined by determining the obtained hardware performance test results of the target hardware and the computing power service requirements. That is, when determining the first optimization strategy, not only the hardware performance test results but also the computing power service requirements are considered. This ensures that after optimizing the edge computing device based on the first optimization strategy, the hardware performance can be fully utilized, effectively solving the problem of domestically produced hardware being difficult to adapt to edge computing devices, while simultaneously improving the real-time performance and stability of the edge computing device.

[0120] In one embodiment, the first determining module is further specifically used for:

[0121] The target hardware is subjected to performance tests on the target indicators to obtain the hardware performance test results; the hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0122] In one embodiment, the second determining module is further specifically used for:

[0123] Based on computing power service requirements and hardware performance test results, determine the peak hardware performance information of the target hardware;

[0124] The hardware performance evaluation results are determined based on the hardware performance test results and hardware performance peak information.

[0125] Based on the hardware performance evaluation results, a first optimization strategy is determined; wherein the first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0126] In one embodiment, the optimization module is further specifically used for:

[0127] The performance of the edge computing device is optimized based on the first optimization strategy to obtain the first edge device;

[0128] During the operation of the first edge device, acquire the hardware operation information of the target hardware;

[0129] Based on hardware operation information, a second optimization strategy is determined;

[0130] The first edge device is optimized based on the second optimization strategy.

[0131] In one embodiment, the optimization module is further specifically used for:

[0132] Based on hardware operation information, the service processing status of the first edge device is determined; the hardware operation information includes processor temperature information, device load information, and memory usage information.

[0133] Determine the resource allocation strategy based on the business processing status;

[0134] Based on the resource allocation strategy, a second optimization strategy is determined.

[0135] In one embodiment, the optimization module is further specifically used for:

[0136] Based on the business processing status, determine the business processing strategy; the business processing strategy includes the business priority allocation strategy, processing thread allocation strategy and transmission strategy for different business types;

[0137] We will use business processing strategies and resource allocation strategies as the second optimization strategies.

[0138] In one embodiment, a device optimization apparatus 1 further includes:

[0139] The acquisition module is used to acquire the optimized device operation information of the first edge device; the device operation information includes data processing time, data processing accuracy, and system failure rate.

[0140] The third determining module is used to determine the optimization result of the first edge device based on the device operation information.

[0141] Each module in the aforementioned equipment optimization device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0142] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 7 As shown, this computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores relevant data about the target hardware and edge computing devices. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a device optimization method.

[0143] Those skilled in the art will understand that Figure 7The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0144] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0145] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0146] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0147] Based on the first optimization strategy, edge computing devices are optimized.

[0148] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the hardware performance test results of the target hardware, including:

[0149] The target hardware is subjected to performance tests on the target indicators to obtain the hardware performance test results; the hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0150] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining a first optimization strategy based on computing power service requirements and hardware performance test results, including:

[0151] Based on computing power service requirements and hardware performance test results, determine the peak hardware performance information of the target hardware;

[0152] The hardware performance evaluation results are determined based on the hardware performance test results and hardware performance peak information.

[0153] Based on the hardware performance evaluation results, a first optimization strategy is determined; wherein the first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0154] In one embodiment, when the processor executes the computer program, it further performs the following steps: optimizing the edge computing device based on a first optimization strategy, including:

[0155] The performance of the edge computing device is optimized based on the first optimization strategy to obtain the first edge device;

[0156] During the operation of the first edge device, acquire the hardware operation information of the target hardware;

[0157] Based on hardware operation information, a second optimization strategy is determined;

[0158] The first edge device is optimized based on the second optimization strategy.

[0159] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining a second optimization strategy based on hardware operating information, including:

[0160] Based on hardware operation information, the service processing status of the first edge device is determined; the hardware operation information includes processor temperature information, device load information, and memory usage information.

[0161] Determine the resource allocation strategy based on the business processing status;

[0162] Based on the resource allocation strategy, a second optimization strategy is determined.

[0163] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining a second optimization strategy based on a resource allocation strategy, including:

[0164] Based on the business processing status, determine the business processing strategy; the business processing strategy includes the business priority allocation strategy, processing thread allocation strategy and transmission strategy for different business types;

[0165] We will use business processing strategies and resource allocation strategies as the second optimization strategies.

[0166] In one embodiment, when the processor executes the computer program, it further performs the following steps: after optimizing the first edge device based on a second optimization strategy, the method further includes:

[0167] Obtain optimized device operation information for the first edge device; the device operation information includes data processing time, data processing accuracy, and system failure rate.

[0168] Based on the equipment operation information, the optimization result of the first edge device is determined.

[0169] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0170] Determine the hardware performance test results of the target hardware; whereby the target hardware is the hardware in the edge computing device.

[0171] Based on computing power service requirements and hardware performance test results, the first optimization strategy is determined;

[0172] Based on the first optimization strategy, edge computing devices are optimized.

[0173] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the hardware performance test results of the target hardware, including:

[0174] The target hardware is subjected to performance tests on the target indicators to obtain the hardware performance test results; the hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0175] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a first optimization strategy based on computing power service requirements and hardware performance test results, including:

[0176] Based on computing power service requirements and hardware performance test results, determine the peak hardware performance information of the target hardware;

[0177] The hardware performance evaluation results are determined based on the hardware performance test results and hardware performance peak information.

[0178] Based on the hardware performance evaluation results, a first optimization strategy is determined; wherein the first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0179] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: optimizing the edge computing device based on a first optimization strategy, including:

[0180] The performance of the edge computing device is optimized based on the first optimization strategy to obtain the first edge device;

[0181] During the operation of the first edge device, acquire the hardware operation information of the target hardware;

[0182] Based on hardware operation information, a second optimization strategy is determined;

[0183] The first edge device is optimized based on the second optimization strategy.

[0184] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a second optimization strategy based on hardware runtime information, including:

[0185] Based on hardware operation information, the service processing status of the first edge device is determined; the hardware operation information includes processor temperature information, device load information, and memory usage information.

[0186] Determine the resource allocation strategy based on the business processing status;

[0187] Based on the resource allocation strategy, a second optimization strategy is determined.

[0188] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a second optimization strategy based on a resource allocation strategy, including:

[0189] Based on the business processing status, determine the business processing strategy; the business processing strategy includes the business priority allocation strategy, processing thread allocation strategy and transmission strategy for different business types;

[0190] We will use business processing strategies and resource allocation strategies as the second optimization strategies.

[0191] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: after optimizing the first edge device based on a second optimization strategy, the method further includes:

[0192] Obtain optimized device operation information for the first edge device; the device operation information includes data processing time, data processing accuracy, and system failure rate.

[0193] Based on the equipment operation information, the optimization result of the first edge device is determined.

[0194] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0195] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the hardware performance test results of the target hardware, including:

[0196] The target hardware is subjected to performance tests on the target indicators to obtain the hardware performance test results; the hardware performance test results include at least one of the following: processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

[0197] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a first optimization strategy based on computing power service requirements and hardware performance test results, including:

[0198] Based on computing power service requirements and hardware performance test results, determine the peak hardware performance information of the target hardware;

[0199] The hardware performance evaluation results are determined based on the hardware performance test results and hardware performance peak information.

[0200] Based on the hardware performance evaluation results, a first optimization strategy is determined; wherein the first optimization strategy includes at least one of the following: algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

[0201] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: optimizing the edge computing device based on a first optimization strategy, including:

[0202] The performance of the edge computing device is optimized based on the first optimization strategy to obtain the first edge device;

[0203] During the operation of the first edge device, acquire the hardware operation information of the target hardware;

[0204] Based on hardware operation information, a second optimization strategy is determined;

[0205] The first edge device is optimized based on the second optimization strategy.

[0206] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a second optimization strategy based on hardware runtime information, including:

[0207] Based on hardware operation information, the service processing status of the first edge device is determined; the hardware operation information includes processor temperature information, device load information, and memory usage information.

[0208] Determine the resource allocation strategy based on the business processing status;

[0209] Based on the resource allocation strategy, a second optimization strategy is determined.

[0210] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining a second optimization strategy based on a resource allocation strategy, including:

[0211] Based on the business processing status, determine the business processing strategy; the business processing strategy includes the business priority allocation strategy, processing thread allocation strategy and transmission strategy for different business types;

[0212] We will use business processing strategies and resource allocation strategies as the second optimization strategies.

[0213] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: after optimizing the first edge device based on a second optimization strategy, the method further includes:

[0214] Obtain optimized device operation information for the first edge device; the device operation information includes data processing time, data processing accuracy, and system failure rate.

[0215] Based on the equipment operation information, the optimization result of the first edge device is determined.

[0216] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0217] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0218] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for optimizing equipment, characterized in that, The method includes: Determine the hardware performance test results of the target hardware; wherein, the target hardware is the hardware in the edge computing device; Based on the computing power service requirements and the hardware performance test results, a first optimization strategy is determined; Based on the first optimization strategy, the edge computing device is optimized.

2. The method according to claim 1, characterized in that, The determination of the hardware performance test results of the target hardware includes: The target hardware is subjected to performance testing on target indicators to obtain hardware performance test results; wherein, the hardware performance test results include at least one of processor processing speed, memory read speed, storage device read / write bandwidth, storage device read / write latency, and network interface transmission rate.

3. The method according to claim 1, characterized in that, The step of determining the first optimization strategy based on computing power service requirements and hardware performance test results includes: Based on the computing power service requirements and the hardware performance test results, determine the peak hardware performance information of the target hardware; Based on the hardware performance test results and the hardware performance peak information, the hardware performance evaluation result is determined; Based on the hardware performance evaluation results, the first optimization strategy is determined; wherein the first optimization strategy includes at least one of the algorithm optimization strategy, code optimization strategy, and cache optimization strategy.

4. The method according to claim 1, characterized in that, The optimization of the edge computing device based on the first optimization strategy includes: Based on the first optimization strategy, the performance of the edge computing device is optimized to obtain a first edge device; During the operation of the first edge device, the hardware operation information of the target hardware is acquired; Based on the hardware operation information, a second optimization strategy is determined; Based on the second optimization strategy, the first edge device is optimized.

5. The method according to claim 4, characterized in that, The step of determining the second optimization strategy based on the hardware operating information includes: Based on the hardware operation information, the service processing status of the first edge device is determined; wherein, the hardware operation information includes processor temperature information, device load information, and memory usage information; Based on the business processing status, determine the resource allocation strategy; Based on the resource allocation strategy, the second optimization strategy is determined.

6. The method according to claim 5, characterized in that, Determining the second optimization strategy based on the resource allocation strategy includes: Based on the business processing status, a business processing strategy is determined; wherein, the business processing strategy includes a business priority allocation strategy, a processing thread allocation strategy, and a transmission strategy for different business types; The business processing strategy and the resource allocation strategy are used as the second optimization strategy.

7. The method according to claim 4, characterized in that, After optimizing the first edge device based on the second optimization strategy, the method further includes: Obtain optimized device operation information of the first edge device; wherein, the device operation information includes data processing time, data processing accuracy, and system failure rate; Based on the device operation information, the optimization result of the first edge device is determined.

8. An equipment optimization device, characterized in that, The device includes: The first determining module is used to determine the hardware performance test results of the target hardware; wherein, the target hardware is the hardware in the edge computing device; The second determining module is used to determine the first optimization strategy based on the computing power service requirements and the hardware performance test results; An optimization module is used to optimize the edge computing device based on the first optimization strategy.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the device optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the device optimization method according to any one of claims 1 to 7.

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