Method and device for determining effective running duration and computer program product

Abstract

The invention provides an effective running time determination method and device, electronic equipment, a storage medium and a computer program product, relates to the technical field of artificial intelligence, in particular to the technical fields of distributed training, large models and the like, and can be applied to distributed training scenes. According to the specific implementation scheme, a power consumption threshold value and a duration threshold value corresponding to a calculation unit are determined through a pre-trained threshold value determination model according to first instantaneous power consumption data of the calculation unit; for second instantaneous power consumption data in the data sequence corresponding to the calculation unit, responding to the situation that the duration of the second instantaneous power consumption data smaller than a power consumption threshold exceeds a duration threshold, and determining a time interval corresponding to the duration as an invalid operation time interval; and according to the invalid operation time interval, determining the effective operation duration of the calculation unit. The accuracy of the power consumption threshold value and the duration threshold value and the adaptation degree of the power consumption threshold value, the duration threshold value and the calculation unit are improved, and then the accuracy of the effective operation duration determined based on the power consumption threshold value and the duration threshold value is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, specifically to technical fields such as distributed training and large models, and in particular to a method, device, electronic device, storage medium and computer program product for determining effective running time, which can be applied in distributed training scenarios. Background Art

[0002] Currently, large-scale model training requires the use of large-scale GPUs (Graphics Processing Units). As a key resource, it is necessary to monitor and analyze the operation status of GPUs. When analyzing and mining the power consumption, temperature, utilization, and other portraits of GPU training, it is necessary to exclude invalid operation time intervals based on the operation of the GPU to determine the effective operation time, which is used to measure the use of the GPU and provide a reference for GPU scheduling. In the prior art, the parameters in the invalid operation time interval determination rule are determined based on business experience. Summary of the invention

[0003] The present disclosure provides a method, device, electronic device, storage medium and computer program product for determining effective operating time.

[0004] According to a first aspect, a method for determining an effective operating time is provided, comprising: determining a power consumption threshold and a duration threshold corresponding to a computing unit according to first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model; for second instantaneous power consumption data in a data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, determining a time interval corresponding to the duration as an invalid operating time interval; and determining the effective operating time of the computing unit according to the invalid operating time interval.

[0005] According to a second aspect, a device for determining an effective operating time is provided, comprising: a threshold determination unit, configured to determine a power consumption threshold and a duration threshold corresponding to a computing unit according to first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model; an interval determination unit, configured to, for second instantaneous power consumption data in a data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, determine a time interval corresponding to the duration as an invalid operating time interval; and a duration determination unit, configured to determine the effective operating time of the computing unit according to the invalid operating time interval.

[0006] According to a third aspect, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method described in any implementation manner of the first aspect.

[0007] According to a fourth aspect, a non-transitory computer-readable storage medium storing computer instructions is provided, where the computer instructions are used to cause a computer to execute the method described in any implementation of the first aspect.

[0008] According to a fifth aspect, a computer program product is provided, comprising: a computer program, which implements the method described in any implementation manner of the first aspect when executed by a processor.

[0009] According to the technology disclosed in the present invention, a method and device for determining effective operating time are provided, which use a threshold determination model to determine the power consumption threshold and duration threshold corresponding to the computing unit according to the instantaneous power consumption data of the computing unit, thereby improving the accuracy of the power consumption threshold and duration threshold, as well as the adaptability of the power consumption threshold, duration threshold and the computing unit; based on the power consumption threshold and duration threshold, the accuracy of the determined invalid operating time interval is improved, thereby improving the accuracy of the effective operating time determined based on the invalid operating time interval.

[0010] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0012] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present disclosure may be applied;

[0013] Figure 2 is a flow chart of an embodiment of a method for determining effective operating time according to the present disclosure;

[0014] Figure 3 A schematic diagram of a dividing line between effective power consumption data and invalid power consumption data according to this embodiment;

[0015] Figure 4 This is a task allocation process based on distributed locks according to this embodiment;

[0016] Figure 5 is a schematic diagram of distribution of second instantaneous power consumption data according to this embodiment;

[0017] Figure 6 is a schematic diagram of an application scenario of the method for determining the effective running time according to this embodiment;

[0018] Figure 7 is a flowchart of another embodiment of a method for determining effective operating time according to the present disclosure;

[0019] Figure 8 is a structural diagram of an embodiment of a device for determining effective operation time according to the present disclosure;

[0020] Fig. 9 It is a schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION

[0021] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0022] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0023] Figure 1 An exemplary architecture 100 is shown to which the effective operation time determination method and apparatus of the present disclosure can be applied.

[0024] like Figure 1 As shown, the system architecture 100 may include data centers 101, 102, 103, a network 104, and a server 105. The communication connection between the data centers 101, 102, 103 constitutes a topological network, and the network 104 is used to provide a medium for communication links between the data centers 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0025] The data centers 101, 102, and 103 include multiple computing units, which may be hardware devices or software that support network connection for data interaction and data processing. When the computing unit is hardware, it may be various electronic devices that support network connection, information acquisition, interaction, processing and other functions, including but not limited to GPU, CPU (Central Processing Unit), etc. When the computing unit is software, it may be installed in the electronic devices listed above. It may be implemented as multiple software or software modules for providing distributed services, or it may be implemented as a single software or software module. No specific limitation is made here.

[0026] Server 105 may be a server that provides various services, for example, a background processing server that determines the effective operation time of computing units according to instantaneous power consumption data of computing units in data centers 101, 102, 103. As an example, server 105 may be a cloud server.

[0027] It should be noted that the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, software or software modules used to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0028] It should also be noted that the method for determining the effective operation time provided in the embodiments of the present disclosure is generally executed by a server. Accordingly, all parts (eg, all units) included in the device for determining the effective operation time are generally all arranged in the server.

[0029] It should be understood that Figure 1 The number of data centers, networks, and servers in the system architecture is only illustrative. Any number of data centers, networks, and servers may be provided as required. When the electronic device on which the effective operation time determination method is executed does not need to perform data transmission with other electronic devices, the system architecture may only include the electronic device (e.g., server) on which the effective operation time determination method is executed.

[0030] Please refer to Figure 2 , Figure 2 A flowchart of a method for determining effective operation time provided by an embodiment of the present disclosure. In process 200, the following steps are included:

[0031] Step 201 , determining a power consumption threshold and a duration threshold corresponding to a computing unit according to first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model.

[0032] In this embodiment, the execution subject of the method for determining the effective running time (for example, Figure 1 The server in the example embodiment can obtain the first instantaneous power consumption data of the computing unit remotely or locally through a wired network connection or a wireless network connection, and determine the power consumption threshold and duration threshold corresponding to the computing unit according to the first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model.

[0033] The computing unit may be a computing unit in various computing scenarios, such as a GPU, a CPU, etc. in a distributed training scenario of a large language model.

[0034] The first instantaneous power consumption data represents the power consumption of the computing unit at a specific time point, and the specific time point can be determined based on a preset time interval. The preset time interval can be specifically set according to actual conditions, and the unit of the preset time interval is, for example, different time units such as seconds, minutes, or hours. For example, the first instantaneous power consumption data represents the instantaneous power consumption of the computing unit collected every one minute.

[0035] The first instantaneous power consumption threshold can be the power consumption data of continuous time series within any historical time period of the computing unit, or it can be the power consumption data of discrete time series. In order to further ensure the accuracy of the power consumption threshold and the duration threshold determined by the threshold determination model, it is necessary to determine that the first instantaneous power consumption threshold and the second instantaneous power consumption data in the subsequent step 202 belong to the same type of application scenario, for example, both are distributed training scenarios for large language models. The types of application scenarios have different levels of division precision. When the accuracy requirements for the power consumption threshold and the duration threshold are higher, it is necessary to ensure that the application scenarios of the first instantaneous power consumption threshold and the second instantaneous power consumption data belong to the same type with higher precision.

[0036] It should be noted that the first instantaneous power consumption data and the second instantaneous power consumption data are both instantaneous power consumption data of the computing unit. Since the first instantaneous power consumption data is used to determine the power consumption threshold and the duration threshold, and the second instantaneous power consumption data is used to determine the invalid operation time interval, the two functions are different, and are distinguished by the first instantaneous power consumption data and the second instantaneous power consumption data. In this embodiment, the possibility that at least part of the data between the first instantaneous power consumption data and the second instantaneous power consumption data is the same is not excluded. For example, 100 first instantaneous power consumption data are part of 10,000 second instantaneous power consumption data.

[0037] The threshold determination model is used to characterize the correspondence between the first instantaneous power consumption data and the power consumption threshold and duration threshold. The first instantaneous power consumption data of the computing unit is input into the pre-trained threshold determination model to generate the power consumption threshold and duration threshold corresponding to the computing unit. For example, the power consumption threshold is 200 watts and the duration threshold is 10 minutes.

[0038] As an example, the above execution subject can train the threshold determination model in the following way:

[0039] First, a training sample set is obtained. The training samples in the training sample set include sample instantaneous power consumption data of the computing unit and labels indicating whether the sample instantaneous power consumption data is invalid operation power consumption data or valid operation power consumption data. The power consumption value of the invalid power consumption data is less than the power consumption threshold, and the power consumption value of the valid power consumption data is greater than or equal to the power consumption threshold.

[0040] Then, a machine learning algorithm is used, with the sample instantaneous power consumption data as input and the label corresponding to the sample instantaneous power consumption data as the expected output, to train a threshold determination model, wherein the threshold determination model is, for example, a support vector machine, a convolutional neural network, a recurrent neural network, or other models.

[0041] In some optional implementations of this embodiment, the execution subject may perform step 201 in the following manner:

[0042] First, a threshold determination model is used to determine a boundary line for dividing the first instantaneous power consumption data into effective power consumption data and invalid power consumption data.

[0043] Continue to refer Figure 3 , showing a schematic diagram of the dividing line between effective power consumption data and invalid power consumption data.

[0044] Assume that the dividing line is expressed by the following formula:

[0045] a×P+b×R+c=0

[0046] Wherein, P represents the power consumption threshold, and R represents the duration threshold. Parameters a, b, and c may be determined based on a threshold determination model.

[0047] The effective power consumption data is represented by solid points, and the ineffective power consumption data is represented by hollow points.

[0048] Then, based on the dividing line, a power consumption threshold and a duration threshold are determined.

[0049] As an example, a point with a high accuracy and a low power consumption value is selected on the dividing line to determine the power consumption threshold and the duration threshold.

[0050] by Figure 3 Taking point T (p1, r1) in as an example, the part with instantaneous power consumption less than p1 and duration greater than r1 is 301. The execution subject can determine the accuracy of point T based on the ratio between the number of hollow points included in 301 and the number of all hollow points. The ratio is positively correlated with the accuracy.

[0051] In this implementation, a specific determination method for power consumption threshold and duration threshold based on a threshold determination model is provided, which further improves the accuracy of power consumption threshold and duration threshold, as well as the adaptability of power consumption threshold, duration threshold and computing unit.

[0052] Step 202: for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, determine the time interval corresponding to the duration as an invalid operation time interval.

[0053] In this embodiment, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, the above-mentioned execution entity can determine the time interval corresponding to the duration as an invalid operation time interval in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold.

[0054] Since the invalid operation time intervals to be determined are continuous in time series, it is necessary to determine the invalid operation time intervals based on the second instantaneous power consumption data that is continuous in time series, that is, the second instantaneous power consumption data in the data sequence.

[0055] As an example, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the data sequence including the second instantaneous power consumption data less than the power consumption threshold, and the duration of the second instantaneous power consumption data less than the power consumption threshold exceeds the duration threshold, the time interval corresponding to the duration is determined as an invalid operation time interval. The time interval corresponding to the duration takes the time starting point corresponding to the duration as the interval starting point, and takes the time end point corresponding to the duration as the interval end point.

[0056] In some examples, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, there may not be second instantaneous power consumption data less than the power consumption threshold, or there may be second instantaneous power consumption data less than the power consumption threshold, but its duration does not exceed the duration threshold. At this time, it is determined that within the time interval corresponding to the data sequence, the computing unit has been running effectively, and there is no invalid running time interval. Among them, the time interval corresponding to the data sequence takes the time point corresponding to the first second instantaneous power consumption data in the data sequence as the interval starting point, and takes the time point corresponding to the last second instantaneous power consumption data in the data sequence as the interval end point.

[0057] In some optional implementations of this embodiment, the execution subject may perform step 202 in the following manner:

[0058] In the first step, for an interval determination node in a node cluster, a target computing unit corresponding to the interval determination node is determined from a computing unit cluster.

[0059] The computing unit cluster includes a large number of computing units, and the second instantaneous power consumption data of the large number of computing units needs to be processed in parallel by multiple interval determination nodes in the node cluster.

[0060] As an example, the execution entity may distribute the data processing tasks corresponding to each computing unit to multiple interval determination nodes in the node cluster based on an average distribution method, thereby determining the corresponding relationship between the interval determination nodes and the computing units.

[0061] As another example, the execution entity may adopt a load balancing strategy to distribute the data processing tasks corresponding to each computing unit to multiple interval determination nodes in the node cluster, thereby determining the correspondence between the interval determination nodes and the computing units.

[0062] In the second step, for the second instantaneous power consumption data in the data sequence corresponding to the target computing unit, through the interval determination node, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, the time interval corresponding to the duration is determined as an invalid running time interval.

[0063] In this implementation, each interval determination node is responsible for processing the second instantaneous power consumption data of the target computing unit corresponding to itself.

[0064] In this implementation, the second instantaneous power consumption data of multiple computing units in the node parallel processing computing unit cluster is determined by multiple intervals in the node cluster, thereby improving data processing efficiency.

[0065] In some optional implementations of this embodiment, the above-mentioned execution subject may also perform the following operation: obtaining a data sequence of the target computing unit within a preset time interval every preset time interval.

[0066] The running time of the computing units in the computing unit cluster may be long. Waiting until the running is completed to process all the second instantaneous power consumption data will increase the computing pressure of the interval determination node and is not conducive to monitoring the running process of the computing unit.

[0067] In this implementation, the data sequence of the target computing unit in the preset time interval is obtained at every preset time interval, and then the data sequence of the preset target computing unit in the time interval is processed in the manner shown in step 202 to obtain the invalid operation time interval. The preset time interval can be specifically set according to the actual situation. For example, the duration of the preset time interval is 60 minutes. Every hour, the data sequence of the computing unit in the past hour is obtained.

[0068] In this implementation, the execution subject may further perform the following operation: merge the invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval, and determine the invalid running time interval of the target computing unit up to the current time interval.

[0069] Merge is used to represent the merging of two adjacent time intervals into one time interval. For example, one invalid running time interval is [0,40], and the other invalid running time interval is [40,55]. The merged interval is [0,55]. After determining the invalid running time interval up to the current time, it can be stored so that the user can view the running status of the computing unit during the training process.

[0070] The complete determination process of the invalid running time interval in the present implementation is as follows: first, every preset time interval, the data sequence of the target computing unit within the preset time interval is obtained; then, for the second instantaneous power consumption data in the data sequence corresponding to the target computing unit, through the interval determination node, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, the time interval corresponding to the duration is determined as an invalid running time interval; finally, the invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval are merged to determine the invalid running time interval of the target computing unit up to the current time.

[0071] In this implementation, on the basis of parallel processing, processing of data sequences is performed at preset time intervals, which helps to further improve data processing efficiency and reduce data processing pressure.

[0072] In some optional implementations of this embodiment, the above-mentioned execution entity can also perform the above-mentioned first step in the following manner: for the interval determination node in the node cluster, a distributed lock mechanism is used to determine the target computing unit corresponding to the interval determination node from the computing unit cluster.

[0073] Continue to refer Figure 4 , which shows the task allocation process based on distributed locks.

[0074] As an example, a distributed lock is set at the GPU granularity, and multiple interval determination nodes compete for the unique identifier of the GPU as the key of the distributed lock. In order to prevent a certain interval determination node from grabbing the data processing tasks of all GPUs, the order of the GPUs is randomly scattered, and different interval determination nodes will grab computing tasks in different orders. The interval determination node processes the preempted computing tasks through a batch processing program. After a preset time (for example, 5 minutes) after the data processing tasks are allocated, the distributed lock is released.

[0075] In this implementation, based on the distributed lock, the orderliness and rationality of the data processing task allocation process are further improved.

[0076] Continue to refer Figure 5 , shows a schematic diagram of the distribution of the second instantaneous power consumption data. In which, the effective power consumption data represents the instantaneous power consumption data greater than or equal to the power consumption threshold; the invalid power consumption data represents the instantaneous power consumption data less than the power consumption threshold.

[0077] In some optional implementations of this embodiment, the execution subject may perform step 202 in the following manner:

[0078] The first step is to iteratively perform the following operations within the target time interval corresponding to the data sequence:

[0079] 1.1, determine the time point corresponding to the first second instantaneous power consumption data less than the power consumption threshold after the target time point as the start time point.

[0080] The target time point corresponding to the first operation is the starting point of the target time interval.

[0081] 1.2, in response to the target time interval including target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point, determining the time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data as the end time point.

[0082] 1.3, in response to the time length between the start time point and the end time point exceeding the duration threshold, determining an invalid running time interval corresponding to the current operation based on the start time point and the end time point.

[0083] 1.4, determine the end time point as the target time point corresponding to the next operation.

[0084] As an example, the target time interval corresponding to the data sequence is [START, END]. In the first operation, first, the time point T1 corresponding to the first second instantaneous power consumption data less than the power consumption threshold after START is determined as the start time point; then, in response to the target time interval including the target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point T1, the time point T2 corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined as the end time point; then, in response to the time length between the start time point T1 and the end time point T2 exceeding the duration threshold, based on the start time point T1 and the end time point T2, the invalid operation time interval [T1, T2] corresponding to the current operation is determined; finally, T2 is determined as the target time point corresponding to the next operation.

[0085] In the second operation, the time point T3 corresponding to the first second instantaneous power consumption data less than the power consumption threshold after T2 is determined as the starting time point, and the above steps are iteratively performed.

[0086] In the second step, the invalid running time intervals corresponding to the operations within the target time interval are merged to determine the invalid running time intervals within the target time interval.

[0087] In this implementation, the invalid running time intervals corresponding to the operations within the target time interval are merged to obtain the invalid running time interval within the target time interval.

[0088] It should be noted that this implementation method can be combined with the above parallel examples. For example, in the above parallel examples, each interval determination node determines the invalid operation time interval of the corresponding target computing node according to the determination method in this implementation method. For another example, in the above parallel examples, the sequence consisting of the second instantaneous power consumption data of the target computing unit collected every preset time interval is used as the data sequence in this implementation method, and the determination method in this implementation method is used to determine the invalid operation time interval of the corresponding target computing node.

[0089] In this implementation, a specific determination method for determining an invalid running time interval is provided, which helps to improve the calculation efficiency and accuracy of the invalid running time interval.

[0090] In some optional implementations of the present embodiment, the execution entity may also execute step 202 in the following manner: in response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point, and the time length between the start time point and the end point of the target time interval exceeding the duration threshold, the invalid running time interval corresponding to the current operation is determined based on the start time point and the end point of the interval.

[0091] Continuing to refer to the above example, in response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point T3, and the time length between the start time point and the interval end point of the target time interval exceeding the duration threshold, then based on the start time point T3 and the interval end point END of the target time interval, the invalid running time interval [T3, END] corresponding to the current operation is determined.

[0092] In this implementation, a method for determining the invalid running time interval in different situations is provided, thereby improving the comprehensiveness of the determination method.

[0093] It should be noted that the following situations may also exist in the process of determining the invalid running time interval:

[0094] 1. There is no second instantaneous power consumption less than the power consumption threshold in the target time interval corresponding to the data sequence, indicating that there is no invalid operation time interval in the target time zone.

[0095] 2. There is a second instantaneous power consumption less than the power consumption threshold in the target time interval corresponding to the data sequence, but the duration of the second instantaneous power consumption is less than the duration threshold, indicating that there is no invalid operation time interval in the target time zone.

[0096] 3. Starting from the starting point of the target time interval, all second instantaneous power consumptions are less than the power consumption threshold, indicating that the target time interval is an invalid operation time interval.

[0097] In some optional implementations of this embodiment, the above execution subject may also perform the following operations:

[0098] Based on the first query interface of the database where the second instantaneous power consumption data is located, the first second instantaneous power consumption data less than the power consumption threshold after the target time point is determined. The first query interface has the function of querying the first data less than a certain value within a certain time period.

[0099] Based on the second query interface of the database, the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined. The first query interface has the function of querying the first data greater than or equal to a certain value within a certain time period.

[0100] In this implementation, the complete process of determining the invalid running time interval is as follows: First, within the target time interval corresponding to the data sequence, iteratively perform the following operations:

[0101] Based on the first query interface of the database where the second instantaneous power consumption data is located, the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point is determined; the time point corresponding to the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point is determined as the start time point, wherein the target time point corresponding to the first operation is the interval starting point of the target time interval; in response to the target time interval including target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point, based on the second query interface of the database, the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined; the time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined as the end time point; in response to the time length between the start time point and the end time point exceeding the duration threshold, based on the start time point and the end time point, the invalid running time interval corresponding to the current operation is determined; and the end time point is determined as the target time point corresponding to the next operation.

[0102] Then, the invalid running time intervals corresponding to the operations within the target time interval are merged to determine the invalid running time interval within the target time interval.

[0103] It should be noted that the present implementation method can also be combined with the above-mentioned parallel example. For example, after determining the target computing unit corresponding to each interval determination node, the invalid running time interval is determined by the determination method in the present implementation method for the second instantaneous power consumption data within the preset time interval obtained every preset time interval.

[0104] In this implementation, all second instantaneous power consumption data are no longer pulled into the server memory of the interval determination node. Instead, data processing is performed based on the query function provided by the database API (Application Programming Interface). This greatly reduces the number and frequency of input / output operations between the interval determination node and the database, thereby improving the data determination efficiency.

[0105] Step 203: Determine the effective running time of the computing unit according to the invalid running time interval.

[0106] In this embodiment, the execution subject may determine the effective running time of the computing unit according to the invalid running time interval.

[0107] Specifically, the invalid running time interval is cut out in the time interval corresponding to the data sequence to obtain the valid running time interval; based on the valid running time interval, the effective running time of the computing unit is determined. For example, the time interval corresponding to the data sequence is [0,40], and the invalid running time interval [10,30] is deleted to obtain the valid running time intervals [0,10] and [30,40]; further, the valid running time intervals [0,10] and [30,40] determine the effective running time to be 20 minutes.

[0108] Continue to see Figure 6 , Figure 6 It is a schematic diagram of an application scenario 600 of the method for determining the effective operation time according to the present embodiment. The server first determines the power consumption threshold and duration threshold corresponding to the computing unit according to the first instantaneous power consumption data of the computing unit through the pre-trained threshold determination model 601; then, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, the time interval corresponding to the duration is determined as an invalid operation time interval 602; according to the invalid operation time interval, the effective operation time of the computing unit is determined.

[0109] In this embodiment, a method for determining effective operation time is provided, which divides the computing units in multiple data centers based on the grouping scales corresponding to multiple parallel computing strategies, improves the rationality of the unit group, and helps to improve the data communication efficiency based on the unit group; based on the sensitivity of the communication data of multiple parallel computing strategies to the communication delay time, controls the interaction of sensitive communication data across data centers, controls the interaction of non-sensitive communication data within the data center, and reduces the impact of communication delays between data centers on the training process. Thus, on the basis of maintaining communication efficiency, based on multiple data centers and multiple parallel computing strategies, the training efficiency of the distributed training process is improved.

[0110] In some optional implementations of this embodiment, the above-mentioned execution subject may further perform the following operations before executing the above-mentioned step 202: first, determine the specified time interval according to the received interval designation instruction; then, in response to the specified time interval including a first sub-interval in which an invalid running time interval has been determined and a second sub-interval in which an invalid running interval has not been determined, determine the data sequence of the computing unit in the second sub-interval.

[0111] After executing step 202, the following operation may be performed: merging the invalid running time interval in the first sub-interval and the invalid running time interval in the second sub-interval to determine the invalid running time interval in the specified time interval.

[0112] In this implementation, the execution subject may perform step 203 in the following manner: determining the effective operation time of the computing unit within the specified time interval according to the invalid operation time interval within the specified time interval.

[0113] Specifically, in the present implementation, the complete process of determining the invalid operating interval is as follows: determining a designated time interval according to a received interval designation instruction; determining a data sequence of the computing unit in the second sub-interval in response to the designated time interval including a first sub-interval in which an invalid operating time interval has been determined and a second sub-interval in which an invalid operating time interval has not been determined; for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, determining the time interval corresponding to the duration as an invalid operating time interval; merging the invalid operating time interval in the first sub-interval and the invalid operating time interval in the second sub-interval to determine an invalid operating time interval in the designated time interval; and determining the effective operating time of the computing unit in the designated time interval based on the invalid operating time interval in the designated time interval.

[0114] In this implementation, the user may have a real-time query demand for effective running time. However, there are some intervals within the specified time interval specified by the user, and the invalid running time interval of the computing unit has not been determined. In the above implementation method of determining the invalid running time interval once every preset time interval, it is assumed that the preset time interval is one hour. The current time is 10:30, and the invalid running time between 10:00 is determined through the above implementation methods. At this time, the user needs to view the effective running time between 9:00-10:30, and the invalid running time between 10:00-10:30 needs to be calculated in real time.

[0115] In this implementation, the execution subject may adopt the invalid operation time interval determination method in each of the implementations to determine the invalid operation time interval of the computing unit in the second sub-interval. As an example, for a specified computing unit indicated by a user, the invalid operation time interval is determined by determining a node corresponding to the specified computing unit and according to the second instantaneous power consumption data of the specified computing unit in the second sub-interval using the iterative calculation method.

[0116] In this implementation, the invalid operation time interval of the computing unit within the user's specified time interval can be determined in real time, thereby improving the convenience of information determination and user experience.

[0117] Continue to refer Figure 7 , shows a schematic process 700 of another embodiment of a method for determining effective running time according to the present disclosure. In process 700, the following steps are included:

[0118] Step 701, determining a power consumption threshold and a duration threshold corresponding to a computing unit according to first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model.

[0119] Step 702: For the interval determination node in the node cluster, determine the target computing unit corresponding to the interval determination node from the computing unit cluster.

[0120] Step 703: Obtain the data sequence of the target computing unit within the preset time interval every preset time interval.

[0121] Step 704, iteratively perform the following operations within the target time interval corresponding to the data sequence:

[0122] Step 7041: Determine the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point based on the first query interface of the database where the second instantaneous power consumption data is located.

[0123] Step 7042: determine the time point corresponding to the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point as the start time point.

[0124] The target time point corresponding to the first operation is the starting point of the target time interval.

[0125] Step 7043, in response to the target second instantaneous power consumption data greater than or equal to the power consumption threshold being included in the target time interval after the start time point, determining the first second instantaneous power consumption data in the target second instantaneous power consumption data based on the second query interface of the database.

[0126] Step 7044: determine the time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data as the end time point.

[0127] Step 7045, in response to the time length between the start time point and the end time point exceeding the duration threshold, determine the invalid running time interval corresponding to the current operation based on the start time point and the end time point.

[0128] Step 7046, determine the end time point as the target time point corresponding to the next operation.

[0129] Step 7047, in response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point, and the time length between the start time point and the interval end point of the target time interval exceeding the duration threshold, determine the invalid running time interval corresponding to the current operation based on the start time point and the interval end point.

[0130] Step 705 , merging the invalid running time intervals corresponding to the operations within the target time interval, and determining the invalid running time intervals within the target time interval.

[0131] Step 706 , merging the invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval, and determining the invalid running time interval of the target computing unit up to the current time interval.

[0132] Step 707: Determine the effective running time of the computing unit according to the invalid running time interval.

[0133] Compared with process 200, process 700 of the method for determining the effective operating time in this embodiment specifically describes the process of determining the power consumption threshold and the duration threshold, the parallel calculation process of the invalid operating time interval, and the data query process during the calculation process. While improving the accuracy of the effective operating time based on the threshold determination model, it also improves the data determination efficiency based on parallel calculation and data query, and can cope with the computing scenarios of large-scale computing units.

[0134] Continue to refer Figure 8As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a device for determining effective operation time. The system embodiment is Figure 2 Corresponding to the method embodiment shown, the system can be specifically applied to various electronic devices.

[0135] like Figure 8 As shown, the effective operation duration determination device 800 includes: a threshold determination unit 801, configured to determine the power consumption threshold and duration threshold corresponding to the computing unit according to the first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model; an interval determination unit 802, configured to, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, determine the time interval corresponding to the duration as an invalid operation time interval; a duration determination unit 803, configured to determine the effective operation duration of the computing unit according to the invalid operation time interval.

[0136] In some optional implementations of this embodiment, the threshold determination unit 801 is further configured to: determine the dividing line for dividing the first instantaneous power consumption data into effective power consumption data and invalid power consumption data through a threshold determination model; and determine the power consumption threshold and duration threshold based on the dividing line.

[0137] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: for an interval determination node in a node cluster, determine a target computing unit corresponding to the interval determination node from the computing unit cluster; for the second instantaneous power consumption data in the data sequence corresponding to the target computing unit, through the interval determination node, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, determine the time interval corresponding to the duration as an invalid running time interval.

[0138] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: obtain a data sequence of the target computing unit within the preset time interval every preset time interval; and merge the invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval to determine the invalid running time interval of the target computing unit up to the current time interval.

[0139] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: for the interval determination node in the node cluster, use a distributed lock mechanism to determine the target computing unit corresponding to the interval determination node from the computing unit cluster.

[0140] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: iteratively perform the following operations within the target time interval corresponding to the data sequence: determine the time point corresponding to the first second instantaneous power consumption data less than the power consumption threshold after the target time point as the start time point, wherein the target time point corresponding to the first operation is the interval starting point of the target time interval; in response to the target time interval including target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point, determine the time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data as the end time point; in response to the time length between the start time point and the end time point exceeding the duration threshold, determine the invalid running time interval corresponding to the current operation based on the start time point and the end time point; determine the end time point as the target time point corresponding to the next operation; and merge the invalid running time intervals corresponding to the operations within the target time interval to determine the invalid running time interval within the target time interval.

[0141] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: in response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point, and the time length between the start time point and the interval end point of the target time interval exceeding the duration threshold, determine the invalid running time interval corresponding to the current operation based on the start time point and the interval end point.

[0142] In some optional implementations of this embodiment, the interval determination unit 802 is further configured to: determine the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point based on the first query interface of the database where the second instantaneous power consumption data is located; and determine the first second instantaneous power consumption data in the target second instantaneous power consumption data based on the second query interface of the database.

[0143] In some optional implementations of this embodiment, the above-mentioned device also includes: an interval designation unit (not shown in the figure), which is configured to determine the designated time interval according to the received interval designation instruction; and the interval determination unit 802 is further configured to: in response to the designated time interval including a first sub-interval in which an invalid running time interval has been determined and a second sub-interval in which an invalid running interval has not been determined, determine the data sequence of the computing unit in the second sub-interval; and merge the invalid running time interval in the first sub-interval and the invalid running time interval in the second sub-interval to determine the invalid running time interval in the designated time interval; and the duration determination unit 803 is further configured to: determine the effective running duration of the computing unit in the designated time interval according to the invalid running time interval in the designated time interval.

[0144] In the present embodiment, a device for determining an effective operating time is provided. Through a threshold determination model, a power consumption threshold and a duration threshold corresponding to the computing unit are determined according to the instantaneous power consumption data of the computing unit, thereby improving the accuracy of the power consumption threshold and the duration threshold, as well as the adaptability of the power consumption threshold, the duration threshold and the computing unit; based on the power consumption threshold and the duration threshold, the accuracy of the determined invalid operating time interval is improved, thereby improving the accuracy of the effective operating time determined based on the invalid operating time interval.

[0145] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can implement the method for determining the effective operating time described in any of the above embodiments when executing.

[0146] According to an embodiment of the present disclosure, the present disclosure further provides a readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to implement the method for determining the effective operating time described in any of the above embodiments when executed.

[0147] An embodiment of the present disclosure provides a computer program product. When the computer program is executed by a processor, the method for determining the effective operating time described in any of the above embodiments can be implemented.

[0148] Fig. 9 A schematic block diagram of an example electronic device 900 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0149] like Fig. 9As shown, the device 900 includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0150] A number of components in the device 900 are connected to the I / O interface 905, including: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; a storage unit 908, such as a disk, an optical disk, etc.; and a communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 909 allows the device 900 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0151] The computing unit 901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 901 performs the various methods and processes described above, such as the determination method of the effective operation time. For example, in some embodiments, the determination method of the effective operation time may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the determination method of the effective operation time described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the determination method of the effective operation time by any other appropriate means (e.g., by means of firmware).

[0152] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable effective runtime determination device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0154] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0155] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0156] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0157] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services; it may also be a server for a distributed system, or a server combined with a blockchain.

[0158] According to the technical solution of the embodiments of the present disclosure, a method and device for determining the effective operating time are provided. Through a threshold determination model, the power consumption threshold and duration threshold corresponding to the computing unit are determined according to the instantaneous power consumption data of the computing unit, thereby improving the accuracy of the power consumption threshold and duration threshold, as well as the adaptability of the power consumption threshold, duration threshold and the computing unit; based on the power consumption threshold and duration threshold, the accuracy of the determined invalid operating time interval is improved, thereby improving the accuracy of the effective operating time determined based on the invalid operating time interval.

[0159] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution provided by this disclosure can be achieved, and this document does not limit this.

[0160] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for determining effective operation time, comprising: Determine, by a pre-trained threshold determination model, a power consumption threshold and a duration threshold corresponding to the computing unit according to first instantaneous power consumption data of the computing unit; For the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, determining the time interval corresponding to the duration as an invalid operation time interval; The effective running time of the computing unit is determined according to the invalid running time interval.

2. The method according to claim 1, wherein: The method of determining the power consumption threshold and duration threshold corresponding to the computing unit by using the pre-trained threshold determination model according to the first instantaneous power consumption data of the computing unit includes: Determining, by means of the threshold determination model, a dividing line for dividing the first instantaneous power consumption data into effective power consumption data and invalid power consumption data; The power consumption threshold and the duration threshold are determined according to the dividing line.

3. The method according to claim 1, wherein: The method of determining, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, a time interval corresponding to the duration as an invalid operation time interval, includes: For an interval determination node in the node cluster, determining a target computing unit corresponding to the interval determination node from the computing unit cluster; For the second instantaneous power consumption data in the data sequence corresponding to the target computing unit, through the interval determination node, in response to the duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, the time interval corresponding to the duration is determined as an invalid running time interval.

4. The method according to claim 3, wherein: For the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, determining the time interval corresponding to the duration as an invalid operation time interval, further comprising: At every preset time interval, acquiring a data sequence of the target computing unit within the preset time interval; and The invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval are combined to determine the invalid running time interval of the target computing unit up to the current time interval.

5. The method according to claim 3, wherein: The step of determining, for an interval determination node in a node cluster, a target computing unit corresponding to the interval determination node from a computing unit cluster, includes: For the interval determination node in the node cluster, a distributed lock mechanism is adopted to determine the target computing unit corresponding to the interval determination node from the computing unit cluster.

6. The method according to any one of claims 1 to 5, wherein: The method of determining, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, a time interval corresponding to the duration as an invalid operation time interval, includes: In the target time interval corresponding to the data sequence, the following operations are iteratively performed: Determine the time point corresponding to the first second instantaneous power consumption data less than the power consumption threshold after the target time point as the start time point, wherein the target time point corresponding to the first operation is the interval starting point of the target time interval; In response to the target time interval including target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point, determining a time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data as an end time point; In response to the time length between the start time point and the end time point exceeding the duration threshold, determining an invalid running time interval corresponding to the current operation based on the start time point and the end time point; Determining the end time point as the target time point corresponding to the next operation; and The invalid running time intervals corresponding to the operations within the target time interval are merged to determine the invalid running time interval within the target time interval.

7. The method according to claim 6, wherein: For the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, determining the time interval corresponding to the duration as an invalid operation time interval, further comprising: In response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point, and the time length between the start time point and the interval end point of the target time interval exceeding the duration threshold, the invalid running time interval corresponding to the current operation is determined based on the start time point and the interval end point.

8. The method according to claim 6, wherein: For the second instantaneous power consumption data in the data sequence corresponding to the computing unit, in response to the duration of the second instantaneous power consumption data being less than the power consumption threshold exceeding the duration threshold, determining the time interval corresponding to the duration as an invalid operation time interval, further comprising: Determine, based on a first query interface of a database where the second instantaneous power consumption data is located, the first second instantaneous power consumption data after the target time point that is less than the power consumption threshold; and Based on the second query interface of the database, the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined.

9. The method according to any one of claims 1 to 8, wherein: Also includes: Determine a designated time interval according to the received interval designation instruction; In response to the designated time interval including a first subinterval in which an invalid operation time interval has been determined and a second subinterval in which an invalid operation time interval has not been determined, determining a data sequence of the computing unit in the second subinterval; and Merging the invalid running time interval in the first sub-interval and the invalid running time interval in the second sub-interval to determine the invalid running time interval in the specified time interval; as well as The determining, according to the invalid running time interval, the effective running time of the computing unit includes: The effective operation time duration of the computing unit within the specified time interval is determined according to the invalid operation time interval within the specified time interval.

10. A device for determining effective operation time, comprising: A threshold determination unit is configured to determine a power consumption threshold and a duration threshold corresponding to the computing unit according to first instantaneous power consumption data of the computing unit through a pre-trained threshold determination model; an interval determination unit configured to, for the second instantaneous power consumption data in the data sequence corresponding to the computing unit, determine, in response to a duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, a time interval corresponding to the duration as an invalid operation time interval; The duration determination unit is configured to determine the effective operation duration of the computing unit according to the invalid operation time interval.

11. The device according to claim 10, wherein: The threshold determination unit is further configured to: The threshold determination model is used to determine a dividing line for dividing the first instantaneous power consumption data into effective power consumption data and invalid power consumption data; and the power consumption threshold and the duration threshold are determined based on the dividing line.

12. The device according to claim 10, wherein: The interval determination unit is further configured to: For an interval determination node in a node cluster, a target computing unit corresponding to the interval determination node is determined from a computing unit cluster; for a second instantaneous power consumption data in a data sequence corresponding to the target computing unit, through the interval determination node, in response to a duration of the second instantaneous power consumption data less than the power consumption threshold exceeding the duration threshold, a time interval corresponding to the duration is determined as an invalid operating time interval.

13. The device according to claim 12, wherein: The interval determination unit is further configured to: At every preset time interval, a data sequence of the target computing unit within the preset time interval is obtained; and the invalid running time interval within the preset time interval and the invalid running time interval of the target computing unit before the preset time interval are merged to determine the invalid running time interval of the target computing unit up to the current time interval.

14. The device according to claim 12, wherein: The interval determination unit is further configured to: For the interval determination node in the node cluster, a distributed lock mechanism is adopted to determine the target computing unit corresponding to the interval determination node from the computing unit cluster.

15. The device according to any one of claims 10 to 14, wherein: The interval determination unit is further configured to: In the target time interval corresponding to the data sequence, the following operations are iteratively performed: the time point corresponding to the first second instantaneous power consumption data less than the power consumption threshold after the target time point is determined as the start time point, wherein the target time point corresponding to the first operation is the interval starting point of the target time interval; in response to the target time interval including the target second instantaneous power consumption data greater than or equal to the power consumption threshold after the start time point, the time point corresponding to the first second instantaneous power consumption data in the target second instantaneous power consumption data is determined as the end time point; in response to the time length between the start time point and the end time point exceeding the duration threshold, based on the start time point and the end time point, an invalid operation time interval corresponding to the current operation is determined; the end time point is determined as the target time point corresponding to the next operation; and The invalid running time intervals corresponding to the operations within the target time interval are merged to determine the invalid running time interval within the target time interval.

16. The device according to claim 15, wherein: The interval determination unit is further configured to: In response to the second instantaneous power consumption data within the target time interval being less than the power consumption threshold after the start time point, and the time length between the start time point and the interval end point of the target time interval exceeding the duration threshold, the invalid running time interval corresponding to the current operation is determined based on the start time point and the interval end point.

17. The device according to claim 15, wherein: The interval determination unit is further configured to: Based on the first query interface of the database where the second instantaneous power consumption data is located, determine the first second instantaneous power consumption data that is less than the power consumption threshold after the target time point; and based on the second query interface of the database, determine the first second instantaneous power consumption data in the target second instantaneous power consumption data.

18. The device according to any one of claims 10 to 17, wherein: Also includes: The interval specifying unit is configured to determine the specified time interval according to the received interval specifying instruction; as well as The interval determination unit is further configured to: In response to the specified time interval including a first subinterval in which an invalid running time interval has been determined and a second subinterval in which an invalid running time interval has not been determined, determining a data sequence of the computing unit in the second subinterval; and combining the invalid running time interval in the first subinterval and the invalid running time interval in the second subinterval to determine the invalid running time interval in the specified time interval; and The duration determination unit is further configured to: The effective operation time duration of the computing unit within the specified time interval is determined according to the invalid operation time interval within the specified time interval.

19. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 9.

20. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 9.

21. A computer program product comprising: A computer program which, when executed by a processor, implements the method according to any one of claims 1 to 9.

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