Device performance detection method and device, apparatus, and storage medium

Abstract

Embodiments of the present disclosure relate to a device performance detection method and device, an apparatus and a storage medium, wherein the device performance detection method comprises: determining at least one task performed by a user equipment in a target use scenario; for any one of the at least one task, obtaining a performance state of the user equipment in a case where the user equipment performs the any one task as a performance evaluation result of the any one task, thereby obtaining performance evaluation results of the at least one task; and fusing the performance evaluation results of the at least one task according to weights of the at least one task in the target use scenario, to obtain a performance evaluation result of the user equipment in the target use scenario. The above technical solution can accurately reflect the user's use experience of the device in different target use scenarios.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a method, apparatus, device, and storage medium for testing device performance. Background Technology

[0002] With the development of computer technology, the application scope of terminal devices has greatly expanded, and they have become indispensable tools in people's daily lives. Device performance is a key factor affecting user experience; therefore, various methods for testing device performance have emerged.

[0003] Currently, the common method for testing equipment performance involves having the equipment perform one or more fixed tasks to obtain test data, and then evaluating the equipment performance based on this data. However, this method cannot accurately reflect the user's experience with the equipment. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, the present disclosure provides a device performance testing method, apparatus, device and storage medium.

[0005] A first aspect of this disclosure provides a device performance testing method, the method comprising:

[0006] Identify at least one task performed by the user equipment in the target usage scenario;

[0007] For any one of the at least one tasks, obtain the performance state of the user device when the user device performs any one task, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0008] Based on the weight of at least one task in the target usage scenario, the performance evaluation results of at least one task are fused to obtain the performance evaluation result of the user device in the target usage scenario.

[0009] A second aspect of this disclosure provides a device performance testing apparatus, the apparatus comprising:

[0010] The first determining module is used to determine at least one task performed by the user equipment in the target usage scenario;

[0011] The first acquisition module is used to acquire the performance status of the user device when the user device performs any one of the at least one tasks, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0012] The fusion module is used to fuse the performance evaluation results of at least one task according to the weight of at least one task in the target use scenario, so as to obtain the performance evaluation result of the user device in the target use scenario.

[0013] A third aspect of this disclosure provides an electronic device, the server comprising: a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the method of the first aspect described above.

[0014] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the method of the first aspect described above.

[0015] A fifth aspect of this disclosure provides a computer program product comprising a computer program / instructions that, when executed by a processor, implement the method described in the first aspect above.

[0016] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0017] This disclosure embodiment can determine at least one task executed by a user device in a target usage scenario; for any one of the at least one tasks, the performance state of the user device is obtained when the user device executes any one task, serving as the performance evaluation result of that task, thereby obtaining the performance evaluation result of at least one task; based on the weights of the at least one task in the target usage scenario, the performance evaluation results of the at least one task are fused to obtain the performance evaluation result of the user device in the target usage scenario. By adopting the above technical solution, when facing different target usage scenarios, performance evaluation results of the user device in different target usage scenarios can be obtained. Furthermore, considering the different importance of different tasks in any target usage scenario, the weights corresponding to the tasks are fully considered when determining the performance evaluation result of the user device in that target usage scenario, thereby improving the accuracy of the performance evaluation result of the device in the target usage scenario. Thus, by adopting the above technical solution, the user's experience with the device in different target usage scenarios can be accurately reflected. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0019] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a device performance testing method provided in an embodiment of this disclosure is shown;

[0021] Figure 2 A flowchart of another device performance testing method provided in this disclosure embodiment is shown;

[0022] Figure 3 A flowchart of yet another device performance testing method provided in this disclosure embodiment is shown;

[0023] Figure 4 A schematic diagram of the structure of a device performance testing apparatus provided in an embodiment of this disclosure is shown;

[0024] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure is shown. Detailed Implementation

[0025] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0026] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0027] In view of the problems mentioned in the background technology, the applicant has found that users actually use the device in a variety of scenarios, and the tasks performed by the device are usually different in different scenarios. Therefore, the existing device performance evaluation results cannot measure the device's performance in different scenarios, that is, they cannot accurately reflect the user's experience of using the device in different scenarios. Therefore, there is an urgent need for a method that can detect the device's performance in different scenarios.

[0028] Based on this, this disclosure provides a method, apparatus, device, and storage medium for testing equipment performance. The method for testing equipment performance will be described in detail below.

[0029] Figure 1A flowchart illustrating a device performance testing method according to an embodiment of this disclosure is shown. This method can be performed by an electronic device. The electronic device can be exemplarily understood as a device such as a mobile phone, tablet computer, laptop computer, desktop computer, or smart TV. Figure 1 As shown, the method provided in this embodiment includes the following steps:

[0030] S110. Determine at least one task performed by the user equipment in the target usage scenario.

[0031] In this embodiment of the disclosure, when a user device is used in different target usage scenarios, the tasks it performs may be different. Therefore, in order to determine the performance evaluation results of the user device in the target usage scenario, it is necessary to determine at least one task performed by the user device in the target usage scenario.

[0032] Specifically, the user equipment can be any device that needs to be tested for performance. For example, the user equipment can include devices such as mobile phones, tablets, and laptops, but is not limited to these.

[0033] Specifically, the target use case can be any use case that a user device may encounter during use. For example, the target use case may include, but is not limited to, scenarios in which a user uses the device to play games, watch videos, record videos, browse web pages, process documents, etc.

[0034] Specifically, user equipment typically includes one or more of the following hardware platforms: a central processing unit (CPU), a graphics processing unit (GPU), input / output (I / O) and memory.

[0035] In the target usage scenario, the data operations performed by the user equipment include data operations related to the target usage scenario performed by various hardware platforms. Therefore, based on the differences in hardware platforms and the different purposes of the data operations, the data operations performed by the user equipment in the target usage scenario can be decomposed into at least one task.

[0036] Accordingly, S110 may include: in the target usage scenario, according to the purpose and the corresponding hardware platform, decomposing the data operation performed by the user equipment into one or more parts, each part being associated with a task, thereby obtaining at least one task performed by the user equipment in the target usage scenario. Thus, different tasks correspond to different purposes, and the hardware platforms used by different tasks may be the same or different.

[0037] For example, when the target usage scenario is a user playing games on a user device, the tasks performed by the user device in the target usage scenario may include: multimedia tasks performed by the CPU, such as video encoding, video decoding, and video compression; image processing tasks performed by the GPU, such as 2D image rendering, 3D image rendering, and image sharpening; at least one related task corresponding to I / O; and at least one related task corresponding to memory, etc. However, it is not limited to these.

[0038] S120. For any one of the at least one tasks, obtain the performance state of the user device when the user device performs any one of the tasks, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0039] In this embodiment of the disclosure, for each of at least one task, the performance state of the user device when the user device performs the task is obtained, and the obtained performance state is used as the performance evaluation result of the task.

[0040] Specifically, performance status is data obtained by processing data operations associated with tasks through the hardware platform of the user device.

[0041] Since performance status can characterize the performance of a user device when performing its corresponding task, it can be used as the performance evaluation result of the corresponding task.

[0042] Specifically, the performance state of a user equipment when performing a certain task is related to the detection indicators of that task. The detection indicators for different tasks can be the same or different, and this is not limited here.

[0043] Specifically, the detection metrics may include response time, number of operations per second, power consumption, etc., but are not limited to these.

[0044] The task response time is the time taken for the user equipment to execute the task once; the task operations per second is the ratio of the number of operations performed by the user equipment to the response time of the task once, which may include, for example, floating-point operations per second (FLOPS), but is not limited to; the task power consumption is the amount of energy consumed by the user equipment to execute the task once.

[0045] In some embodiments, S120 may include: obtaining the performance status of the user device when the user device is executing any one of the at least one preset task, thereby obtaining the performance status of the at least one preset task; and filtering out the performance status corresponding to any one task from the performance status of the at least one preset task.

[0046] Specifically, the preset task is the task obtained after deduplicating multiple candidate tasks.

[0047] Specifically, multiple usage scenarios are pre-defined, and for each usage scenario, all tasks that the user device performs in that usage scenario are determined. By taking the union of all tasks performed by the user device in each usage scenario, multiple candidate scenarios can be obtained.

[0048] For example, determine the tasks performed by the user device in a gaming scenario, a video watching scenario, a video recording scenario, a web browsing scenario, and a document processing scenario; take the union of the tasks performed by the user device in each of these usage scenarios to obtain multiple candidate scenarios.

[0049] It is understandable that among the tasks performed by a user device in different usage scenarios, there may be at least one overlapping task. For example, a user device will perform video decoding tasks in both gaming and video watching scenarios. Therefore, multiple candidate tasks can be deduplicated to obtain the preset task.

[0050] Specifically, for each preset task, the user equipment can pre-execute the preset task to obtain the performance status of the user equipment under the execution of the preset task, thereby obtaining the performance status of the user equipment under the execution of each preset task.

[0051] Understandably, the above method can quickly obtain the performance status of the user device when performing any task. Furthermore, when detecting the performance evaluation results of the user device in multiple different target usage scenarios, the user device does not need to repeatedly execute the overlapping tasks in the multiple target usage scenarios, which helps to improve detection efficiency.

[0052] In some other embodiments, S110 may include receiving the performance status of the user equipment when the user equipment is performing any one of the tasks, sent by other electronic devices.

[0053] Specifically, other electronic devices can be user equipment or other electronic devices besides user equipment; no limitation is made here.

[0054] S130. Based on the weight of at least one task in the target usage scenario, fuse the performance evaluation results of at least one task to obtain the performance evaluation result of the user device in the target usage scenario.

[0055] Specifically, the weights are used to characterize the degree of impact of the task on the performance of the user device in the target usage scenario.

[0056] In some embodiments, S130 may include: weighted summation of the performance status of at least one task and the weights of at least one task in the target usage scenario to obtain the performance evaluation result of the user device in the target usage scenario.

[0057] For example, a user device executes tasks A, B, and C in a target usage scenario. Task A's performance status is response time TA, and its weight is a%. Task B's performance status is response time TB, and its weight is b%. Task C's performance status is response time TC, and its weight is c%. Therefore, the performance evaluation result of the user device in the target usage scenario is TA × a% + TB × b% + TC × c%. The same logic applies when performance status is operations per second and power consumption, which will not be elaborated here.

[0058] In other embodiments, S120 may include: determining the detection score corresponding to the performance status of each task based on the correlation between performance status and task performance score; and weighted summing of the detection scores of all tasks and the corresponding weights of the tasks to obtain the performance evaluation result of the user device in the target usage scenario.

[0059] Specifically, electronic devices can pre-store the correlation between performance status and task performance scores, but are not limited to this.

[0060] For example, a user device executes task A, task B, and task C in a target usage scenario. The performance status of task A is the response time TA, and the task performance score corresponding to the response time TA is the score. a Task A has a weight of a%; the performance status of task B is number of operations per second. b / s, number of operations per second b The task performance score corresponding to / s is score b Task B has a weight of b%; the performance status of task C is power consumption WC, and the task performance score corresponding to power consumption WC is score. c If task C has a weight of c%, then the performance evaluation result of the user device in the target usage scenario is score. a ×a%+score b ×b%+score c×c%.

[0061] This disclosure embodiment can determine at least one task executed by a user device in a target usage scenario; for any one of the at least one tasks, the performance state of the user device is obtained when the user device executes any one task, serving as the performance evaluation result of that task, thereby obtaining the performance evaluation result of at least one task; based on the weights of the at least one task in the target usage scenario, the performance evaluation results of the at least one task are fused to obtain the performance evaluation result of the user device in the target usage scenario. By adopting the above technical solution, when facing different target usage scenarios, performance evaluation results of the user device in different target usage scenarios can be obtained. Furthermore, considering the different importance of different tasks in any target usage scenario, the weights corresponding to the tasks are fully considered when determining the performance evaluation result of the user device in that target usage scenario, thereby improving the accuracy of the performance evaluation result of the device in the target usage scenario. Thus, by adopting the above technical solution, the user's experience with the device in different target usage scenarios can be accurately reflected.

[0062] In another embodiment of this disclosure, obtaining the performance state of the user equipment when the user equipment performs any one of the tasks includes:

[0063] S121. Determine the hardware platform used when the user equipment performs any task, thereby obtaining the hardware platform type of any task.

[0064] S122. Determine the performance metrics of any task based on the hardware platform type of any task.

[0065] S123. Obtain the performance status of the user device when it executes any task in the target usage scenario based on the performance index of any task.

[0066] Specifically, when a user device performs a task, the hardware platform type of the hardware platform used for the data operations associated with that task is the hardware platform type of the task.

[0067] For example, if the hardware platform used for a 2D image rendering task is a GPU, then the hardware platform type for the 2D image rendering task is GPU.

[0068] In some embodiments, S121 may specifically include: determining the hardware platform type of the task based on the association between the task and the hardware platform used.

[0069] Specifically, the relationship between a task and the hardware platform used can be pre-stored in the electronic device, but is not limited to this.

[0070] In other embodiments, S121 may specifically include: for each task, determining the hardware platform type of the task based on the hardware platform type identifier carried in the performance status of the task.

[0071] Specifically, the hardware platform type identifier is used to identify the hardware platform used by the task corresponding to the performance state. For example, the hardware platform type identifier 00 can identify that the hardware platform used by the task corresponding to the performance state is CPU, 01 can identify that the hardware platform used by the task corresponding to the performance state is GPU, 10 can identify that the hardware platform used by the task corresponding to the performance state is I / O, and 11 can identify that the hardware platform used by the task corresponding to the performance state is memory, but it is not limited to these.

[0072] Specifically, the detection indicators for different hardware platform types can be the same or different, and no restrictions are imposed here.

[0073] In some embodiments, S121 may specifically include: determining the detection index corresponding to the hardware platform type; and determining the detection index corresponding to the hardware platform type of the task as the detection index of the task.

[0074] Specifically, the detection indicators corresponding to a hardware platform type can be determined based on the correlation between the hardware platform type and the detection indicators. The correlation between the hardware platform type and the detection indicators can be pre-stored in the electronic device, but is not limited to this.

[0075] Specifically, S123 may include: obtaining the performance status of the user device in terms of the performance indicators of the task when the user device performs the task in the target usage scenario.

[0076] Understandably, in practical applications, users may focus on different metrics when executing tasks on different hardware platforms. For example, for CPUs, users may focus more on the number of operations per second, while for GPUs, users may focus more on response time. Therefore, determining the task's metrics based on the hardware platform type allows for flexible setting of appropriate metrics that users are more concerned about.

[0077] Figure 2 This illustration shows a flowchart of another device performance testing method provided by an embodiment of the present disclosure. This embodiment is an optimization based on the above embodiments, and can be combined with various optional solutions from one or more of the above embodiments.

[0078] like Figure 2 As shown, the device performance testing method may include the following steps.

[0079] S210. Determine at least one task performed by the user equipment in the target usage scenario.

[0080] Specifically, S210 and S110 are similar, and no further details are provided here.

[0081] S220. For any one of the at least one tasks, obtain the performance state of the user device when the user device performs any one of the tasks, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0082] Specifically, S210 and S120 are similar, and no further details are provided here.

[0083] S230. Obtain the preset task parameters corresponding to any task.

[0084] Specifically, task parameters are the parameters used in the calculation when normalizing the performance state of a task. The task parameters for different tasks can be the same or different; this is not limited here.

[0085] In some embodiments, for each task, those skilled in the art can determine the task parameters corresponding to the task based on the performance status of multiple calibrated devices when performing the task, but are not limited thereto.

[0086] Specifically, for each task, the selection criteria for multiple calibration devices can be that at least two calibration devices have different performance states when performing the task. For example, all devices on the market that can perform the task can be used as calibration devices, or all models of devices manufactured by the manufacturer corresponding to the user equipment can be used as calibration devices, but it is not limited to these.

[0087] S240. Normalize the performance evaluation result of any task according to the task parameters corresponding to any task, and obtain the task performance score corresponding to the performance evaluation result of any task, thereby obtaining the task performance score of at least one task.

[0088] Specifically, for each task, the performance status of the task can be normalized according to the task parameters corresponding to the task, and the task performance score corresponding to the performance status of the task can be obtained.

[0089] Specifically, the calculation formula used to normalize the performance status based on the task parameters may include logarithmic functions or linear functions, but is not limited to these, as long as normalization can be achieved.

[0090] For example, when the detection metric is response time, the calculation formula used to normalize the performance status based on task parameters can be as follows:

[0091]

[0092] Among them, TX The response time of task X; score X Let α be the task performance score corresponding to the performance state of task X, that is, the task performance score corresponding to task X; α and β are the task parameters corresponding to task X.

[0093] The determination of α and β can be achieved as follows: Multiple calibration devices are pre-selected; for each calibration device, the response time when executing task X is obtained, resulting in multiple response times; the maximum and minimum response times are selected from these multiple response times; α and β are determined based on the maximum response time, the task performance score corresponding to the maximum response time, the minimum response time, and the task performance score corresponding to the minimum response time; where the task performance score corresponding to the maximum response time is less than the task performance score corresponding to the minimum response time, thus normalizing the task performance score between the task performance score corresponding to the minimum response time and the task performance score corresponding to the maximum response time.

[0094] For example, when the performance metric is the number of operations per second, the calculation formula used to normalize the performance status based on the task parameters can be as follows:

[0095]

[0096] Where, number X / s represents the number of operations per second for task X; score X α represents the task performance score corresponding to the performance state of task X; α and β are the task parameters corresponding to task X.

[0097] The determination of α and β is similar to that when the detection index is response time, so it will not be repeated here.

[0098] S250. The performance scores of at least one task and the weights of at least one task in the target usage scenario are weighted and summed to obtain the device performance score of the user device in the target usage scenario.

[0099] Specifically, the device performance score of the user device in the target usage scenario can be calculated based on the following formula:

[0100] score sence =∑ X score X ×ω X

[0101] Among them, score sence The score represents the device performance score of a user device in the target usage scenario. X ω represents the task performance score corresponding to the performance state of task X. XThe weight of task X in the target usage scenario.

[0102] Understandably, with technological advancements, device performance increases rapidly. For example, Moore's Law states that CPU performance doubles every 18 months, meaning CPU performance grows exponentially. This leads to a rapid increase in task performance scores corresponding to the CPU's performance status during task execution. The same applies to other hardware platforms. Thus, compared to a device from a relatively short period (e.g., six months ago), the current device's performance score in its target usage scenario increases dramatically. Consequently, the performance score ranges for low-end, mid-range, and high-end devices defined a short period ago (e.g., six months ago) are no longer applicable. For instance, a low-end device six months ago might have had a performance score between 10,000 and 30,000, while a current low-end device might have a score between 10,000 and 80,000. This results in frequent changes to the performance score ranges for low-end, mid-range, and high-end devices. Without defined performance score ranges for low-end, mid-range, and high-end devices, users would only know that a device with a score of 40,000 is more powerful than a device with a score of 30,000, making it difficult to determine whether a device is high-end or low-end based solely on its performance score.

[0103] However, in this embodiment of the disclosure, by normalizing the performance status according to the task parameters, the rapid increase of the device performance score can be suppressed. In this way, the device performance score ranges corresponding to low-end, mid-range, and high-end devices defined based on the device performance score do not need to be frequently adjusted, so that the device performance score can intuitively reflect the device performance.

[0104] The device performance detection method provided in this disclosure normalizes the performance status according to task parameters to obtain a task performance score corresponding to the performance status. Then, it weights and sums the task performance scores of at least one task with their respective weights in the target usage scenario to obtain the device performance score. This allows the user device's device performance score to intuitively reflect the user device's performance without frequently adjusting the device performance score ranges corresponding to different device levels. Furthermore, by weighting and summing the task performance scores of all tasks with their respective weights, the method fully considers the impact of different tasks on the user device's performance in the target usage scenario, thereby making the device performance score more accurately reflect the user device's performance in the target usage scenario.

[0105] In another embodiment of this disclosure, the process of determining the weight of at least one task in a target use scenario includes:

[0106] S260. Obtain the total number of tasks for at least one task, and the hardware platform type for any one task.

[0107] S270. Determine the weight of any task in the target usage scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks for at least one task.

[0108] Specifically, the total number of tasks is the sum of all tasks executed by the user device in the target usage scenario.

[0109] Specifically, the method for determining the hardware platform type of the task can be found in the previous text, and will not be repeated here.

[0110] Specifically, the number of tasks corresponding to a hardware platform type is the sum of all tasks executed by the user device using the hardware platform corresponding to that hardware platform type in the target usage scenario.

[0111] It should be noted that if a user device needs to perform the same task N times (N is an integer greater than 1) in the target usage scenario, then when counting the total number of tasks and the number of tasks corresponding to the hardware platform type, this task can be regarded as a single task.

[0112] In some embodiments, S270 may include: determining the ratio of the number of tasks corresponding to the hardware platform type to the total number of tasks as the weight of the task corresponding to the hardware platform type in the target usage scenario.

[0113] In some other embodiments, S270 may include: determining the ratio of the number of tasks corresponding to the hardware platform type to the total number of tasks as the hardware platform weight corresponding to the hardware platform type; determining the weight of each task corresponding to the hardware platform type in the target usage scenario based on the hardware platform weight corresponding to the hardware platform type, wherein the sum of the weights of each task corresponding to the hardware platform type in the target usage scenario is equal to the hardware platform weight corresponding to the hardware platform type.

[0114] Understandably, the number of tasks varies across different hardware platform types in the target application scenario, indicating that the performance of different hardware platforms has different impacts on the performance of user devices in the target usage scenario. Therefore, by determining the weight of each task in the target usage scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks, we can ensure that when the hardware platform has a greater impact on the performance of user devices in the target usage scenario, the tasks executed by the hardware platform have a greater weight in the target usage scenario, and thus have a greater impact on the final determined device performance score of user devices in the target usage scenario. This allows the final determined device performance score to more accurately reflect the performance of user devices in the target usage scenario.

[0115] In another embodiment of this disclosure, S270 may include: determining a target task to be executed by the user equipment in a target usage scenario, wherein the target task is a first priority task among at least one task; determining the weight of any task in the target usage scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks of at least one task, wherein the weight of the target task is greater than the weight of other tasks in the target hardware platform type used.

[0116] Specifically, first-priority tasks refer to those that play a crucial role in the performance of the user device in the target usage scenario. For example, the performance of the user device in the target usage scenario often depends on its weaknesses in that scenario, and tasks related to those weaknesses can be considered first-priority tasks.

[0117] Specifically, those skilled in the art can predetermine the target tasks in each scenario and determine the relationship between the scenario and the target tasks.

[0118] Specifically, the relationship between a scenario and a target task can be pre-stored in an electronic device so that the electronic device can obtain the target task in the target usage scenario based on the relationship between the scenario and the target task, but it is not limited to this.

[0119] Specifically, the type of hardware platform used by the target task is the target hardware platform type.

[0120] Specifically, the weights of other tasks in the target hardware platform type can be the same or different, and this is not limited here.

[0121] Specifically, the weight of the target task can be greater than or less than the weight of the task corresponding to the hardware platform type with the most tasks; no limitation is made here.

[0122] It can be understood that, in the target usage scenario, the performance status of the target device when performing the target task plays an important role in the performance of the user device in the target usage scenario. Therefore, by setting the weight of the target task to be greater than the weight of other tasks in the target hardware platform type, the performance status of the target task can have a greater impact on the final determined device performance score of the user device in the target usage scenario, thereby making the final determined device performance score more accurately reflect the performance of the user device in the target usage scenario.

[0123] In another embodiment of this disclosure, the process of determining the weight of a task includes: S280, obtaining the number of times the user device executes any task in the target usage scenario, and using it as the number of times any task is executed; S290, determining the weight of any task in the target usage scenario based on the number of times any task is executed and the total number of times at least one task is executed.

[0124] Specifically, by summing the execution counts for each task, we can obtain the total execution count for all tasks, that is, the total execution count for at least one task.

[0125] Specifically, for each task, the ratio of the number of times the task is executed to the total number of times all tasks are executed can be used to determine the weight of the task in the target use scenario. However, it is not limited to this. As long as the number of times the task is executed is higher, the weight of the task will be greater.

[0126] It can be understood that, in the target usage scenario, the more times a task is executed, the greater the impact of the user device's performance status in executing that task on the target usage scenario. Therefore, by determining the weight of each task based on the number of executions of different tasks and the total number of executions of all tasks, the performance status of tasks with more executions can have a greater impact on the final determined device performance score of the user device in the target usage scenario. This further makes the final determined device performance score more accurately reflect the performance of the user device in the target usage scenario.

[0127] Figure 3 This illustration shows a flowchart of another device performance testing method provided by an embodiment of the present disclosure. This embodiment is an optimization based on the above embodiments, and can be combined with various optional solutions from one or more of the above embodiments.

[0128] like Figure 3 As shown, the performance testing of this device may include the following steps.

[0129] S310. Determine at least one task performed by the user equipment in the target usage scenario.

[0130] Specifically, S310 is similar to S110, and will not be described in detail here.

[0131] S320. For any one of the at least one tasks, obtain the performance state of the user device when the user device performs any one of the tasks, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0132] Specifically, S320 is similar to S120, and will not be described in detail here.

[0133] S330. Based on the weight of at least one task in the target usage scenario, fuse the performance evaluation results of at least one task to obtain the performance evaluation result of the user device in the target usage scenario.

[0134] Specifically, S330 is similar to S130, and will not be described in detail here.

[0135] S340. Based on the performance evaluation results of any task and the weight of any task, generate task performance data for any task.

[0136] In some embodiments, S340 may include: S341, determining the task performance score corresponding to the performance status (i.e., performance evaluation result) of each task, and obtaining the task performance score of the task; S342, for each task, generating task performance data for each task based on the task performance score of the task and the weight of the task in the target use scenario.

[0137] Optionally, S341 may include: obtaining preset task parameters corresponding to any one task; normalizing the performance evaluation result of any one task according to the task parameters corresponding to any one task, obtaining the task performance score corresponding to the performance evaluation result of any one task, thereby obtaining the task performance score of at least one task.

[0138] Optionally, S342 may include: for each task, multiplying the task performance score of the task by the weight of the task in the target use scenario to obtain the task performance data of the task.

[0139] S350: Determine the hardware platform type for any task.

[0140] For details on the specific implementation of S350, please refer to the previous text, which will not be repeated here.

[0141] S360 generates platform performance data for different hardware platform types based on the task performance data of one or more tasks corresponding to different hardware platform types.

[0142] In some embodiments, S360 may include: for each hardware platform type, summing the performance data of one or more tasks corresponding to the hardware platform type to obtain the performance data of the hardware platform type.

[0143] In other embodiments, S360 may include: for each hardware platform type, determining the average value of the performance data of one or more tasks corresponding to the hardware platform type as the performance data of the hardware platform type.

[0144] S370: Obtain hardware usage information for the target usage scenario based on platform performance data of different hardware platform types.

[0145] Specifically, the hardware usage information for the target usage scenario refers to the information about the hardware used by the user device in the target usage scenario. For example, it may include the hardware platform type used by the user device in the target usage scenario, the performance data of each hardware platform type, and the parameters of each hardware platform type (such as model and manufacturer), but it is not limited to these.

[0146] For example, the hardware usage information of user equipment A under target usage scenario A, target usage scenario B, and target usage scenario C obtained after testing user equipment A is shown in Table 1 below:

[0147] Table 1

[0148]

[0149] The device performance testing method provided in this disclosure generates performance data for different hardware platform types and obtains hardware usage information for the target usage scenario based on the performance data of different hardware platform types. This allows users to have a clearer and more detailed understanding of the hardware usage information of the user device in the target usage scenario, making it easier for users to select suitable devices according to their own needs.

[0150] Figure 4 A schematic diagram of a device performance testing apparatus provided in an embodiment of this disclosure is shown. This device performance testing apparatus can be understood as the aforementioned electronic device or a functional module within the aforementioned electronic device. Figure 4 As shown, the equipment performance testing device 400 includes:

[0151] The first determining module 410 is used to determine at least one task performed by the user equipment in the target usage scenario;

[0152] The first acquisition module 420 is used to acquire the performance state of the user device when the user device performs any one of the at least one tasks, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0153] The fusion module 430 is used to fuse the performance evaluation results of at least one task according to the weight of at least one task in the target usage scenario, so as to obtain the performance evaluation result of the user device in the target usage scenario.

[0154] In another embodiment of this disclosure, the first acquisition module 420 may include: a first determination submodule, used to determine the hardware platform used when the user equipment performs any task, thereby obtaining the hardware platform type of any task;

[0155] The second determination submodule is used to determine the performance indicators of any task based on the hardware platform type of any task.

[0156] The first acquisition submodule is used to obtain the performance status of the user device when the user device performs any task in the target usage scenario, based on the performance indicators of any task.

[0157] In yet another embodiment of this disclosure, the fusion module 430 may include:

[0158] The second acquisition submodule is used to acquire preset task parameters corresponding to any task;

[0159] The normalization processing submodule is used to normalize the performance evaluation result of any task based on the task parameters corresponding to any task, and obtain the task performance score corresponding to the performance evaluation result of any task, thereby obtaining the task performance score of at least one task.

[0160] The weighted summation submodule is used to sum the task performance scores of at least one task and the weights of at least one task in the target use scenario to obtain the device performance score of the user device in the target use scenario.

[0161] In another embodiment of this disclosure, the apparatus further includes a second determining module for determining the weight of at least one task in a target use scenario. The second determining module may include:

[0162] The third acquisition submodule is used to acquire the total number of tasks for at least one task, as well as the hardware platform type of any task.

[0163] The third determination submodule is used to determine the weight of any task in the target use scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks for at least one task.

[0164] In another embodiment of this disclosure, the third determining submodule may include:

[0165] The first determining unit is used to determine the target task executed by the user equipment in the target usage scenario, wherein the target task is a task with the first priority among at least one task;

[0166] The second determining unit is used to determine the weight of any task in the target usage scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks of at least one task, wherein the weight of the target task is greater than the weight of other tasks in the target hardware platform type used.

[0167] In another embodiment of this disclosure, the apparatus further includes a second determining module for determining the weight of at least one task in a target use scenario. The second determining module may include:

[0168] The fourth acquisition submodule is used to acquire the number of times the user device executes any task in the target usage scenario, and use this number as the execution count of any task.

[0169] The fourth determination submodule is used to determine the weight of any task in the target use scenario based on the number of times any task is executed and the total number of times at least one task is executed.

[0170] In another embodiment of this disclosure, the device further includes:

[0171] The first generation module is used to generate task performance data for any task based on the performance evaluation results of any task and the weight of any task.

[0172] The third determination module is used to determine the hardware platform type for any task;

[0173] The second generation module is used to generate platform performance data for different hardware platform types based on the task performance data of one or more tasks corresponding to different hardware platform types.

[0174] The second acquisition module is used to obtain hardware usage information for the target usage scenario based on platform performance data of different hardware platform types.

[0175] The apparatus provided in this embodiment can execute the methods of any of the above embodiments, and its execution method and beneficial effects are similar, so they will not be described again here.

[0176] In addition to the methods and apparatus described above, this disclosure also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to implement the network access control method described in this disclosure.

[0177] This disclosure also provides a computer program product, which includes a computer program / instruction. When the computer program / instruction is executed by a processor, it implements the network access control method described in this disclosure.

[0178] This disclosure also provides an electronic device, which includes: a memory storing a computer program; and a processor for executing the computer program, wherein when the computer program is executed by the processor, it can implement the methods of any of the above embodiments.

[0179] Example, Figure 5A schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure is shown. Please refer to the following for details. Figure 5 The diagram illustrates a structural schematic suitable for implementing the electronic device 900 in the embodiments of this disclosure. The electronic device 900 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0180] like Figure 5 As shown, electronic device 900 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 901, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 902 or a program loaded from storage device 908 into random access memory (RAM) 903. RAM 903 also stores various programs and data required for the operation of electronic device 900. Processing device 901, ROM 902, and RAM 903 are interconnected via bus 904. Input / output (I / O) interface 905 is also connected to bus 904.

[0181] Typically, the following devices can be connected to I / O interface 905: input devices 906 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 907 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 908 including, for example, magnetic tapes, hard disks, etc.; and communication devices 909. Communication device 909 allows electronic device 900 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 900 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0182] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 909, or installed from a storage device 908, or installed from a ROM 902. When the computer program is executed by a processing device 901, it performs the functions defined in the methods of embodiments of this disclosure.

[0183] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, 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 device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0184] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0185] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0186] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: determine at least one task to be performed by the user device in a target usage scenario;

[0187] For any one of the at least one tasks, obtain the performance state of the user device when the user device performs any one task, and use it as the performance evaluation result of any one task, thereby obtaining the performance evaluation result of at least one task.

[0188] Based on the weight of at least one task in the target usage scenario, the performance evaluation results of at least one task are fused to obtain the performance evaluation result of the user device in the target usage scenario.

[0189] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0190] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0191] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0192] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0193] 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.

[0194] This disclosure also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the methods of any of the above embodiments. The execution method and beneficial effects are similar, and will not be described again here.

[0195] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0196] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for testing equipment performance, characterized in that, include: Determine at least one task executed by a user equipment in a target usage scenario, wherein the at least one task is obtained by decomposing the data operation based on the purpose of the data operation performed by the user equipment in the target usage scenario and the hardware platform used; For any one of the at least one tasks, the performance state of the user equipment is obtained when the user equipment performs the at least one task, and this is used as the performance evaluation result of the at least one task, thereby obtaining the performance evaluation result of the at least one task. Based on the weights of the at least one task in the target usage scenario, the performance evaluation results of the at least one task are fused to obtain the performance evaluation result of the user device in the target usage scenario, wherein the weights are used to characterize the degree of influence of the task on the performance of the user device in the target usage scenario.

2. The method according to claim 1, characterized in that, The step of obtaining the performance status of the user equipment when the user equipment performs any one of the tasks includes: Determine the hardware platform used when the user equipment performs any one of the tasks, thereby obtaining the hardware platform type of the any one task; The performance metrics of any one task are determined based on the hardware platform type of any one task. The performance status of the user device is obtained based on the performance metrics of any one of the tasks, when the user device performs any one of the tasks in the target usage scenario.

3. The method according to claim 1, characterized in that, Based on the weights of the at least one task in the target usage scenario, the performance evaluation results of the at least one task are fused to obtain the performance evaluation result of the user equipment in the target usage scenario, including: Obtain the preset task parameters corresponding to any one of the tasks; Based on the task parameters corresponding to any one of the tasks, the performance evaluation result of any one of the tasks is normalized to obtain the task performance score corresponding to the performance evaluation result of any one of the tasks, thereby obtaining the task performance score of the at least one task. The device performance score of the user device in the target usage scenario is obtained by weighted summation of the task performance scores of the at least one task and the weights of the at least one task in the target usage scenario.

4. The method according to claim 1, characterized in that, The process of determining the weight of the at least one task in the target use scenario includes: Obtain the total number of tasks for the at least one task, and the hardware platform type for any one task; The weight of any one task in the target usage scenario is determined based on the number of tasks corresponding to different hardware platform types and the total number of tasks for the at least one task.

5. The method according to claim 4, characterized in that, The step of determining the weight of any one task in the target usage scenario based on the number of tasks corresponding to different hardware platform types and the total number of tasks for the at least one task includes: Determine the target task to be executed by the user equipment in the target usage scenario, wherein the target task is a first priority task among the at least one task; The weight of any one task in the target usage scenario is determined based on the number of tasks corresponding to different hardware platform types and the total number of tasks of the at least one task, wherein the weight of the target task is greater than the weight of other tasks in the target hardware platform type used.

6. The method according to claim 1, characterized in that, The process of determining the weight of the at least one task in the target use scenario includes: The number of times the user device executes any one of the tasks in the target usage scenario is obtained, and this number is taken as the number of times the any one task is executed. The weight of any one task in the target use scenario is determined based on the number of times each task is executed and the total number of times each task is executed.

7. The method according to any one of claims 1-6, characterized in that, Also includes: Based on the performance evaluation results of any one of the tasks and the weight of any one of the tasks, generate the task performance data of any one of the tasks; Determine the hardware platform type for any one of the tasks; Based on the task performance data of one or more tasks corresponding to different hardware platform types, generate platform performance data for different hardware platform types; Based on the platform performance data of the different hardware platform types, obtain the hardware usage information for the target usage scenario.

8. A device for testing equipment performance, characterized in that, include: The first determining module is used to determine at least one task executed by the user equipment in a target usage scenario, wherein the at least one task is obtained by decomposing the data operation based on the purpose of the data operation executed by the user equipment in the target usage scenario and the hardware platform used. The first acquisition module is used to acquire, for any one of the at least one tasks, the performance state of the user equipment when the user equipment performs the at least one task, as the performance evaluation result of the at least one task, thereby obtaining the performance evaluation result of the at least one task. The fusion module is used to fuse the performance evaluation results of the at least one task according to the weight of the at least one task in the target use scenario to obtain the performance evaluation result of the user device in the target use scenario, wherein the weight is used to characterize the degree of influence of the task on the performance of the user device in the target use scenario.

9. An electronic device, characterized in that, include: A processor and a memory, wherein the memory stores a computer program that, when executed by the processor, performs the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1-7.

11. A computer program product, characterized in that, The computer program product includes a computer program / instruction that, when executed by a processor, implements the method as described in any one of claims 1-7.

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