Task processing method, electronic equipment and system

Abstract

The invention provides a task processing method, electronic equipment and system, and the method comprises the steps: obtaining the equipment information of a plurality of processing equipment in response to obtaining a target task, and enabling the processing equipment to be connected with the electronic equipment or to be connected with the electronic equipment; based on task information of the target task and the device information, a target processing device group is determined from the multiple processing devices, the target processing device group is used for executing the target task, and the target processing device group comprises at least one of the multiple processing devices; wherein the target processing equipment group can dynamically change along with the change of the execution demand of the target task.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing, and in particular to a task processing method, electronic equipment, and system. Background Art

[0002] In related technologies, task processing usually involves the use of linked machines. If too many machines are used to process tasks, the machine performance and lifespan will be reduced, while using too few machines will extend the task processing time. Therefore, the current linked machines have the problem of unreasonable matching when processing tasks. Summary of the Invention

[0003] The present disclosure provides a task processing method, electronic device, and system to at least solve the above technical problems existing in the prior art.

[0004] According to a first aspect of the present disclosure, there is provided a task processing method, comprising:

[0005] In response to obtaining the target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with the electronic device;

[0006] determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices;

[0007] The target processing device group can change dynamically as the execution requirements of the target task change.

[0008] In one embodiment, it further includes:

[0009] Determining demand change information of the execution demand of the target task based on the task information or target reference data;

[0010] The configuration parameters of the target processing device group are updated based on the demand change information.

[0011] In one embodiment, the determining of the demand change information of the execution requirement of the target task based on the task information or target reference data includes at least one of the following:

[0012] Determining demand change information of the execution demand of the target task based on task information of executed tasks and / or tasks to be executed in the target task;

[0013] Using a first processing model to generate and process task information of executed tasks and / or tasks to be executed in the target task to obtain the demand change information;

[0014] Performing corresponding processing on the obtained target reference data using a second processing model to obtain the demand change information, wherein the target reference data includes target input data of the target user acting on the electronic device and / or operation change data of the processing device;

[0015] Target reference data is obtained, and the demand change information is determined in a corresponding manner based on a source of the target reference data.

[0016] In one embodiment, determining the demand change information of the execution demand of the target task based on the task information of the executed tasks and / or the tasks to be executed in the target task includes at least one of the following:

[0017] Determining a task progress of the target task based on task information of executed tasks among the target tasks, and generating demand change information of an execution demand of the target task based on the task progress;

[0018] generating demand change information of the execution demand of the target task based on at least one of the task type, task amount, and task priority of the task to be executed in the target task;

[0019] The task progress represented by the executed tasks in the target task and at least one of the task type, task amount, and task priority of the task to be executed are input into the first processing model for generation processing to obtain the demand change information of the execution demand.

[0020] In one possible implementation, determining the demand change information in a corresponding manner based on the source of the target reference data includes at least one of the following:

[0021] In a case where the target reference data comes from first input data applied by a target user to an electronic device, determining the first input data as the demand change information, wherein the first input data is used to adjust an execution strategy of the target task, the execution strategy being related to configuration parameters of the target device group;

[0022] In a case where the target reference data is derived from second input data applied by a target user to an electronic device, generating and processing the second input data using a second processing model to obtain the demand change information, wherein the second input data includes feedback data or evaluation data on execution results of executed tasks in the target task;

[0023] In a case where the target reference data comes from operation change data of the processing equipment obtained by monitoring the target processing equipment group, the operation change data is processed using a second processing model to obtain the demand change information;

[0024] When the target reference data comes from environmental change data of the environment in which the target processing device group is located and / or newly added tasks to be processed, the second processing model is used to generate and process the environmental change data and / or the tasks to be processed to obtain the demand change information.

[0025] In one embodiment, updating the configuration parameters of the target processing device group based on the demand change information includes at least one of the following:

[0026] updating at least one of the configuration type, configuration quantity, and collocation combination of the processing devices in the target processing device group based on the demand change information;

[0027] adjusting the operating parameters and / or the assigned tasks of at least one processing device in the target processing device group based on the demand change information;

[0028] The target weight parameter of the third processing model is adjusted based on the demand change information to update the configuration parameters of the target processing device group, wherein the third processing model is a model for determining the target processing device group from a plurality of processing devices.

[0029] In some embodiments, determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information includes:

[0030] determining a task level of the target task based on the task information;

[0031] determining a target configuration weight of target device information of a processing device based on the task level;

[0032] Obtaining score data of at least two processing device groups under the target configuration weight, wherein at least one of the type, quantity, and collocation combination of the processing devices in different processing device groups is different;

[0033] A target processing device group is determined from the at least two processing device groups based on the scoring data.

[0034] In some embodiments, determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information includes at least one of the following:

[0035] inputting the task information and the device information into a third processing model deployed on the electronic device, so as to output a target processing device group determined from a plurality of processing devices using the third processing model;

[0036] The target processing devices are selected from the plurality of processing devices based on a matching relationship between the target task and the target processing device determined by the task information and the device information to form the target processing device group.

[0037] According to a second aspect of the present disclosure, an electronic device is provided, comprising at least one processor and at least one processing model capable of running on the processor, wherein the processing model can be called by a target application to perform at least one of the following:

[0038] In response to obtaining the target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with the electronic device;

[0039] determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices;

[0040] The target processing device group can change dynamically as the execution requirements of the target task change.

[0041] According to a third aspect of the present disclosure, a task processing system is provided, comprising an electronic device and a plurality of processing devices connected to the electronic device, wherein:

[0042] After the electronic device obtains the target task, the electronic device obtains device information of the plurality of processing devices based on the connection;

[0043] as well as,

[0044] determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices;

[0045] The target processing device group can change dynamically as the execution requirements of the target task change.

[0046] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method described in the present disclosure.

[0047] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become readily understood by reading the detailed description below with reference to the accompanying drawings, in which several embodiments of the present disclosure are shown by way of example and not limitation, wherein:

[0049] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

[0050] Figure 1 A schematic diagram showing the steps of the task processing method according to an embodiment of the present disclosure is shown;

[0051] Figure 2 Another step diagram of the task processing method according to an embodiment of the present disclosure is shown;

[0052] Figure 3 A schematic diagram of the structure of a task processing system according to an embodiment of the present disclosure is shown;

[0053] Figure 4 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0054] To make the purposes, features, and advantages of the present disclosure more apparent and understandable, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present disclosure without creative work shall fall within the scope of protection of the present disclosure.

[0055] The following describes a task processing method, electronic device, and system provided by the present application in conjunction with the accompanying drawings.

[0056] like Figure 1 As shown, the present application provides a task processing method, the method comprising:

[0057] S101 : In response to obtaining a target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with an electronic device.

[0058] The task processing method provided in this application is applied to electronic devices. Among them, the electronic device can be a smart terminal or other control device, such as a mobile phone, a personal digital assistant (PAD), a tablet computer, a laptop computer, a desktop computer, etc. The task processing method provided in this application also involves a processing device. The processing device can be a smart terminal or a server. For example, the smart terminal can be a laptop computer, a tablet computer, a desktop computer, a smart phone, a dedicated messaging device, a portable gaming device, a smart speaker, a smart watch, etc. This application does not limit this.

[0059] In this application, a target task can be any task performed by a processing device. For example, the target task can be a data processing task, a multimedia processing task, or a machine learning task. Data processing tasks can include data encryption or decryption. Multimedia processing tasks can include image generation, video generation, audio processing, image rendering, or game rendering. Machine learning tasks can include model training and natural language processing.

[0060] The target task can be obtained through a user input command, for example, a user inputs an image rendering command or a video generation command to an electronic device. The target task can also be obtained through other connected terminal devices, such as mobile phones and desktop computers. For example, a terminal device sends a screen projection task or an audio playback task to an electronic device.

[0061] In this application, the equipment information of the processing equipment may include the historical usage information of the processing equipment, equipment configuration information, current usage status of the equipment, equipment tag information, equipment life information, equipment carbon emission information, etc. Among them, the historical equipment usage information includes the date of use, location of use, usage status (usage time and whether the use status is good), etc.; equipment tag information includes the equipment name, equipment model, equipment commissioning time, etc.; equipment life information includes natural life, economic life, etc.; equipment carbon emission information includes emissions generated by the electricity or heat consumed by the processing equipment during use, etc.

[0062] In this application, an electronic device can establish a connection with multiple processing devices. When the electronic device receives a target task, it obtains device information of the multiple processing devices connected to the electronic device. For example, the devices connected to or capable of establishing a connection with the electronic device include device A, device B, and device C. After receiving the target task, the electronic device of this application obtains device information of device A, device B, and device C. It should be noted that at least one of the multiple processing devices can process the target task.

[0063] For example, in the case of model training, after receiving instructions from a user or terminal device, the electronic device parses or extracts the model training task from the instruction, and obtains the device information of the processing device connected to the electronic device based on the model training task. In the case of image generation, after receiving instructions from a user or terminal device, the electronic device obtains the image generation task, and obtains the device information of multiple processing devices connected to the electronic device based on the image generation task.

[0064] S102 : Determine a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, wherein the target processing device group includes at least one of the plurality of processing devices.

[0065] In this application, after the electronic device obtains the target task, it analyzes the target task and obtains the task information of the target task. The task information of the target task may include the task name (such as model training, image generation, etc.), task type (such as scheduled task, data processing task, user request task, etc.), task completion degree (such as task progress), task urgency (urgent, normal, easy), task source (user or terminal device) and task amount (completed task amount, uncompleted task amount), etc.

[0066] The electronic device determines a target processing device group capable of processing the target task based on the analyzed task information of the target task and the acquired device information. The target processing device group is a combination of devices used to perform the target task. For example, the devices connected or capable of establishing a connection with the electronic device include device A, device B, and device C. The target processing device group for performing the target task can be a device group consisting of devices A and B, a device group consisting of devices A and C, a device group consisting of devices A, B, and C, or a single device among devices A, B, and C.

[0067] For example, using model training as an example, the task information for model training may include: the task name is model training, the task type is image classification, the task volume can be a set training cycle, and the task objective is an accuracy evaluation metric. The multiple processing devices include device A, device B, and device C. Based on the model training task information and device information, if the device group consisting of devices A and B is capable of performing the model training task, the target processing device group is determined to be the device group consisting of devices A and B. The target processing device group consisting of devices A and B is then used to train the image classification model.

[0068] It should be noted that, depending on the target task, the electronic device in this application determines a different target processing device group based on the task information and device information of the target task.

[0069] For example, for image generation, the task information might include: the task name is Image Generation, the task type is Text to Image, and the task objective is Designing an Adaptation Diagram for a Character. Based on the image generation task information and device information, it is determined that either device A or device B can perform the image generation task.

[0070] It is understood that depending on the target task, the electronic device can first determine a target processing device group capable of performing the target task based on the task information and device information of the target task. Based on multiple processing device groups capable of performing the target task, any processing device group capable of performing the target task can be selected for execution. For example, in image generation, device A can be selected to perform the task, or device B can be selected to perform the task. The execution efficiency of device A and device B in performing the target task may differ.

[0071] In the present application, the target processing device group can change dynamically as the execution requirements of the target task change.

[0072] If the execution requirements of the target task change, the target processing device group also needs to be adjusted. The execution requirements of the target task can be operations that determine the need to adjust the device group configuration based on the changes in the target task. For example, it can be based on the life of the processing equipment, the energy-saving carbon emissions of the processing equipment, and the reduction of the operating time of the processing equipment. Then, the operation of adjusting the device group configuration is generated based on the priority sorting. The execution requirements of the target task can also be operations to adjust the device group configuration generated by the dynamic changes of the target processing device group with the machine operating status, environmental changes, network, other task information, or feedback information. The dynamic changes of the target processing equipment can be to adjust the quantity, adjust the task allocation of the processing equipment, adjust the type or combination of the processing equipment, or adjust the working hours of the processing equipment.

[0073] For example, taking model training as an example, when model training is performed, ensuring the life of the processing equipment is the highest priority. The combination of device A and device B can complete the model training with less damage to the processing equipment, thereby ensuring the life of the processing equipment. Therefore, when training the model, a target processing device group consisting of device A and device B can be used. During the model training process, if the ambient temperature rises, the electronic device generates an operation to adjust the device group configuration based on the increase in ambient temperature, and adjusts the target processing device group based on this requirement. For example, device A that cannot operate in a high-temperature environment can be replaced with device C that can operate in a high-temperature environment.

[0074] The task processing method provided by the present application is that after obtaining the target task, the electronic device first obtains the device information of the processing device that is connected or capable of establishing a connection with the electronic device, thereby determining the target processing device group that performs the target task from multiple processing devices based on the task information and device information of the target task. In this application, the target task execution requirements are different, and the target processing device group can dynamically change in accordance with the target task execution requirements. The present application can match the processing devices in the target processing device group according to the different target task execution requirements, so that the linked machine can obtain a reasonable machine match when processing the task. Reasonable machine matching can extend the life of the machine.

[0075] In some embodiments, such as Figure 2 As shown, the task processing method provided by this application also includes:

[0076] S201, determining demand change information of the execution demand of the target task based on the task information or target reference data;

[0077] S202: Update configuration parameters of the target processing device group based on the demand change information.

[0078] During the execution of the target task, the task information will change as the target task progresses, causing changes in the execution requirements of the target task. Based on these changes, an operation is generated to determine whether the device group configuration needs to be adjusted. Changes in task information can include changes in task progress, the type of subtasks to be executed within the target task, the task volume, the urgency of the task, and so on. Changes in task information cause changes in the execution requirements of the target task, thus generating an operation to adjust the device group configuration.

[0079] The target reference data in this application can be the adjustment data of the target task input by the user during the execution of the target task. The adjustment data can be data manually adjusted by the user, for example, in an image processing task, the user manually adjusts the image size, crops the image, or retouches the image. The target reference data can also be a feedback signal during the execution of the target task, and the electronic device determines the demand change information of the target task execution demand after receiving the feedback signal. For example, during the model training process, when the model training task fails to operate normally, a feedback signal will be sent to the electronic device for fault feedback.

[0080] Target reference data can also be used to automatically generate actions that require adjustments to device group configurations based on machine operating status, environmental changes, network, and other task information. For example, if a processing device fails to operate due to a fault, or a processing device has no network signal, or an ambient temperature is too high or too low, causing the processing device to malfunction, or a processing device is unable to perform the target task due to other tasks, or a processing device has a fault alarm or its current operating parameters are abnormal, then adjustments to the device group configuration may be necessary.

[0081] After obtaining information about changes in the execution requirements for a target task, the electronic device can update the configuration parameters of the target processing device group. Updating the configuration parameters of the target processing device group can include, for example, modifying the number of processing devices in the target processing device group, adjusting the types of processing devices, adjusting the combination of processing devices, adjusting the hardware parameters of processing devices, adjusting the task allocation of processing devices, and adjusting the operating hours of processing devices. Modifying the number of processing devices in the target processing device group can include adding device A to a combination of device A and device B. Adjusting the type of processing device can include replacing device A with device C. Adjusting the combination of processing devices can include changing the combination of device A and device B to a combination of device A and device C, or to a combination of device A, device B, and device C. Adjusting the hardware parameters of processing devices can include increasing the processor frequency in device A to produce an overclocked device A. Adjusting the task allocation of processing devices can include swapping the assigned tasks of device A and device B, or transferring the tasks of device A to device C. Adjusting the operating hours of processing devices can include extending the operating hours of devices A and B to complete the target task if the target task cannot be completed within the specified time.

[0082] For example, consider identifying and locating objects in an image as the target task. Identifying objects in an image is one subtask, and locating objects in an image is another. First, identify the object in the image, using a combination of devices A, B, and C to perform this subtask. If, during task execution, it is found that the task progress is too slow and cannot be completed within the specified time, device A can be configured to overclock the hardware, resulting in higher task efficiency. To further increase task processing efficiency, the number of overclocked devices A can be increased to improve task execution efficiency. Alternatively, if device B generates an alarm signal due to excessively high ambient temperature during task execution, device D can be used to replace device B. After completing the subtask of identifying objects in an image, the electronic device can switch to locating objects in an image, depending on the subtask to be performed. The target processing device group can be changed. For example, if device E is required to locate the object in the image but not device A, device E can be added to the target processing device group and device A removed. When identifying objects in an image, the user can also input manual data. For example, to retouch an object in the image, the electronic device determines the retouching requirements based on the manual data and adds device F to the target processing device group. Device F has the function of retouching processing, thereby performing the task of retouching the object in the image.

[0083] In some embodiments, determining the demand change information of the execution requirement of the target task based on the task information or target reference data includes at least one of the following:

[0084] Determining demand change information of the execution demand of the target task based on task information of executed tasks and / or tasks to be executed in the target task;

[0085] Using a first processing model to generate and process task information of executed tasks and / or tasks to be executed in the target task to obtain the demand change information;

[0086] Performing corresponding processing on the obtained target reference data using a second processing model to obtain the demand change information, wherein the target reference data includes target input data of the target user acting on the electronic device and / or operation change data of the processing device;

[0087] Target reference data is obtained, and the demand change information is determined in a corresponding manner based on a source of the target reference data.

[0088] In the present application, the demand change information of the execution demand of the target task can be obtained based on the task information of the tasks that have been executed and / or the tasks to be executed in the target task. For example, the task information can be based on the task progress or the type of subtask to be executed, the task amount, the task urgency, etc. to automatically generate the change information of the execution demand. For example, the target task is to crop and retouch the image, and after cropping, the image will perform the retouching task to generate the target processing device group configuration of the corresponding task type. Or the urgency of the target task changes from easy to urgent to generate the target processing device group configuration.

[0089] In this application, a first processing model is provided in the electronic device. The first processing model can analyze the already executed tasks and the tasks to be executed in the target task and generate demand change information for the execution requirements of the target task. The first processing model can be a large model or AI model pre-installed on the end of the electronic device. The large model or AI model can generate demand change information based on changes in task information.

[0090] In this application, the electronic device has a second processing model that can analyze the target reference data and generate demand change information for the execution requirements of the target task. The second processing model can be a large model or AI model pre-installed on the end of the electronic device, which can generate demand change information based on changes in task information.

[0091] In the present application, the corresponding demand change information can also be determined based on the source of the target parameter data according to the source of the acquired target reference data. The source of the target reference data can be the feedback signal of the processing device during the execution of the task perceived by the electronic device, or it can be the adjustment data input by the user to the electronic device. When the source of the target reference data is the adjustment data input by the user to the electronic device, the electronic device can directly obtain the demand change information based on the adjustment data. If the electronic device receives a feedback signal from the processing device, or actively perceives environmental changes, or receives other tasks, the feedback signal of the processing device, or actively perceives environmental changes, or receives other task information, can be input into the second processing model to obtain demand change information.

[0092] For example, taking image processing as an example, the target task in image processing is to crop and retouch the image. In an electronic device, if the image has been cropped and the retouching task is to be continued, the demand change information can be determined as the change from executing the image cropping task to executing the retouching task. The task information of the executed task and / or the task to be executed can be directly input into the first processing model to obtain the change from executing the image cropping task to executing the retouching task. After obtaining the target reference data, it is determined whether the source of the target reference data is the environmental change actively perceived by the electronic device or the acceptance of other tasks. If the target reference data is a change in ambient temperature, the second processing model in the electronic device is used to obtain the demand change information based on the change in ambient temperature; or if the target reference data is adjustment data input by the user, and the adjustment data requires retouching another target object in the image, the electronic device can directly obtain the demand change information for retouching another target object in the image based on the adjustment data.

[0093] In some embodiments, determining the demand change information of the execution demand of the target task based on the task information of the executed tasks and / or the tasks to be executed in the target task includes at least one of the following:

[0094] Determining a task progress of the target task based on task information of executed tasks among the target tasks, and generating demand change information of an execution demand of the target task based on the task progress;

[0095] generating demand change information of the execution demand of the target task based on at least one of the task type, task amount, and task priority of the task to be executed in the target task;

[0096] The task progress represented by the executed tasks in the target task and at least one of the task type, task amount, and task priority of the task to be executed are input into the first processing model for generation processing to obtain the demand change information of the execution demand.

[0097] In this application, the completion degree of the target task can be determined by the task information of the executed tasks in the target task, and the demand change information of the target task execution requirement can be obtained based on the change of the task completion degree. For example, if the target task includes multiple subtasks, the completed subtasks and the uncompleted subtasks can be determined first, and the device group matching and configuration can be adjusted based on the completion degree of each subtask.

[0098] For example, identifying and locating a target object in an image can be two pending subtasks. Once identification is complete, the pending subtask changes to locating the target object. The task load can be the amount of the target task that has not yet been completed. A change in task urgency can occur when the target task is initially difficult to complete within the preset timeframe, resulting in an urgent urgency. However, as the target task progresses, it becomes clear that the task can be completed within the scheduled timeframe, or even that there is still time left after completion, resulting in a change in urgency to normal or easy.

[0099] In this application, the task type, task amount or task priority of the task to be performed in the target task can be determined, and the demand change information of the execution demand of the target task can be generated. For example, the task type can be raw image or raw video, image processing, speech recognition, image rendering, text generation, etc., and it is determined whether the number of devices in the processing device group needs to be adjusted, the collocation, etc., according to the different task types, to adapt to the task type of the task to be performed. According to the amount of completed tasks or the amount of unfinished tasks, it can be determined whether to adjust the machine running time, energy conservation and emission reduction, life priority, etc., and then adjust the equipment group collocation and configuration. Adjust the equipment group collocation and configuration based on the task priority (urgency or importance, etc.).

[0100] For example, if model training is not urgent, the lifespan of the processing equipment can be prioritized. If the model training task is urgent, the operating speed of the machines in the target processing equipment group is prioritized. If the model training task is not urgent, that is, the task progress has been largely completed, the carbon emissions of the machines in the target processing equipment group are prioritized. Based on the changes in the execution requirements of these target tasks, the configuration and arrangement of the processing equipment group are adjusted.

[0101] In this application, the task progress represented by the executed tasks in the target task and at least one of the task type, task amount, and task priority of the task to be executed can be input into the first processing model for generation processing to obtain demand change information of the execution demand.

[0102] For example, after obtaining the completion degree of the target task or considering the urgency of the subtask to be executed or the task type or task amount based on the task execution progress, this information is input into the first processing model, and the first processing model can directly generate the adjustment operations that need to be performed on the target processing device group.

[0103] In some embodiments, determining the demand change information in a corresponding manner based on the source of the target reference data includes at least one of the following:

[0104] In a case where the target reference data comes from first input data applied by a target user to an electronic device, determining the first input data as the demand change information, wherein the first input data is used to adjust an execution strategy of the target task, the execution strategy being related to configuration parameters of the target device group;

[0105] In a case where the target reference data is derived from second input data applied by a target user to an electronic device, generating and processing the second input data using a second processing model to obtain the demand change information, wherein the second input data includes feedback data or evaluation data on execution results of executed tasks in the target task;

[0106] In a case where the target reference data comes from operation change data of the processing equipment obtained by monitoring the target processing equipment group, the operation change data is processed using a second processing model to obtain the demand change information;

[0107] When the target reference data comes from environmental change data of the environment in which the target processing device group is located and / or newly added tasks to be processed, the second processing model is used to generate and process the environmental change data and / or the tasks to be processed to obtain the demand change information.

[0108] If the target reference data is first input data input by the user to the electronic device, it can be determined whether the device group configuration needs to be adjusted based on the first input data, thereby adjusting the target processing device group according to the need to adjust the device group configuration.

[0109] For example, in the first task scenario, if the task urgency is normal, priority is given to ensuring the long life of the target processing equipment group. At this time, the task can be achieved by combining device A and device B. The combination of device A and device B can complete the model training with less damage to the processing equipment, thereby ensuring the life of the processing equipment.

[0110] In the second task scenario, the task is urgent and prioritizing reducing the machine's runtime. In this case, the frequency parameters of device A and device B can be modified. For example, device A and / or device B can be converted to overclocked devices to reduce the runtime of the processing devices. A combination of overclocked device A and overclocked device B can also be used, or a target processing device group consisting of devices A, B, and C can be used to perform the model training task. This is because the combination of overclocked devices A and B can efficiently complete the model training task and reduce the device's runtime. Alternatively, device D can be added to the device group consisting of devices A and B to perform the model training task, speeding up the processing of the model training task and reducing the runtime of the processing device.

[0111] In the third scenario, the task has been confirmed to be completed ahead of schedule, and the focus can be on reducing energy consumption and carbon emissions from processing equipment. In this case, the combination of devices A and C is suitable, as this combination produces lower carbon emissions. It is understood that the model training task can be completed with combinations of devices A and B, A and C, A, B, and C, A, B, and C, or C and D.

[0112] If the target reference data comes from the second input data of the target user to the electronic device, the second input data includes the evaluation data input by the user and the feedback data or evaluation data of the point-and-shoot device on the execution results of the executed tasks in the target task.

[0113] Exemplarily, the second input data may be the user's satisfaction with the currently completed task or a positive or negative evaluation, such as it consumes too much electricity; based on the user's evaluation, the electronic device generates an operation to adjust the configuration of the device group with the goal of energy conservation and emission reduction, so as to adjust the target processing device group; if the user's evaluation is that the task progress is slow, the electronic device can generate an operation to adjust the configuration of the device group with the goal of improving the task processing speed based on the evaluation data.

[0114] If the target reference data is derived from operational change data of a processing device in the target processing device group, an operation to adjust the device group configuration is obtained based on the change data using a second processing model in the electronic device. The operational change data of the processing device may include abnormalities or failures of the processing device, disconnection, poor network status, etc.

[0115] For example, during image generation, device A is used to perform the image generation task. If device A is unable to connect to the mobile communication network due to network reasons, such as a wireless network disconnection, the electronic device can disconnect device A and use device B, which can connect to the mobile communication network, to continue the image generation task. If device B is performing other tasks, device C can be used to continue the image generation task.

[0116] Wherein, if the target reference data comes from the environmental change data of the environment in which the target processing device group is located and / or the newly added tasks to be processed, the second processing model is used to generate and process the environmental change data and / or the tasks to be processed to obtain demand change information. Wherein, the environmental change data may include spatial environment change data such as temperature and humidity changes, processing equipment online or offline, and network environment change data such as changes in bandwidth and signal connection stability. The newly added tasks to be processed may include processing tasks other than the target tasks,

[0117] For example, during model training, a device group consisting of device A and device B is used to perform the model training task. Due to environmental reasons, such as excessively high temperature, the operating state of device B cannot meet the requirements of model training, and an alarm message appears. The electronic device can then control device B to stop running, and use a device group consisting of device A and device C to continue performing the model training task. Alternatively, during model training, another task is added to the electronic device, and the target processing device group needs to be reconfigured or another target processing device group can be added. If the other task is related to model training, such as image classification, the target processing device group is reconfigured. If the other task is not related to model training, such as image retouching, another target processing device group can be set to process the image retouching.

[0118] In some embodiments, updating the configuration parameters of the target processing device group based on the demand change information includes at least one of the following:

[0119] updating at least one of the configuration type, configuration quantity, and collocation combination of the processing devices in the target processing device group based on the demand change information;

[0120] adjusting the operating parameters and / or the assigned tasks of at least one processing device in the target processing device group based on the demand change information;

[0121] The target weight parameter of the third processing model is adjusted based on the demand change information to update the configuration parameters of the target processing device group, wherein the third processing model is a model for determining the target processing device group from a plurality of processing devices.

[0122] The demand change information for adjusting the configuration of the device group according to the change of the target task can modify the processing devices in the target processing device group. The demand change information can modify the configuration type, configuration quantity or combination of the processing devices.

[0123] For example, if the target task of an electronic device changes from image processing to model training, since the computing power involved in image processing is relatively weak, the computing power of the processing devices in the corresponding target processing device group is relatively weak. If the target task changes to model training, the processing devices in the target processing device group need to be replaced with devices with stronger processing power. Alternatively, if the target task of the electronic device is completed slowly and needs to be accelerated, the number of processing devices in the target processing device group can be increased. If the type of target task changes, for example, image processing is changed to video output, the combination of processing devices in the target processing device group can be changed, such as changing the combination of device A and device B to the combination of device A and device C.

[0124] The demand change information can also be used to update the operating parameters and assigned tasks of the processing devices in the target processing device group. Operating parameters can include controller frequency, voltage, and current for the processing devices. Assigned tasks can include image processing, image classification, and image positioning. When image positioning is required after image classification, demand change information is generated. Based on this need for image positioning, the processing device combination or tasks in the target device group can be adjusted.

[0125] For example, if during model training, the task progress is too slow and cannot be completed within the specified time, you can configure device A to be overclocked. This will increase the task efficiency. You can also increase the running time of device A to ensure that the model training task is completed within the specified time. Alternatively, you can increase the number of overclocked devices A to improve task execution efficiency. Alternatively, you can add other devices, such as device B, to distribute the target task workload between devices A and B, thereby increasing the speed of model training.

[0126] The target weight parameter of the third processing model is adjusted based on the target task's demand change information, so that the third processing model can determine the configuration parameters of the target processing device group, and determine the target processing device group from the plurality of processing devices based on the configuration parameters. The target weight parameter can be set for the third processing model based on the target task's requirements. For example, if the target task's requirements involve factors such as the target task's computational time, machine life, load overhead, and carbon emissions, the target weight parameter can be a weighted proportion of factors such as computational time, machine life, load overhead, and carbon emissions.

[0127] Depending on the urgency of the task, different factors are considered, and the weighting of multiple factors varies. For example, when the task urgency is normal, the priority is to ensure the longevity of the machine combination. In this case, machine life can be the primary factor, and computing time, load overhead, and carbon emissions can be used as subsidiary factors. In this case, the weighting of computing time, machine life, load overhead, and carbon emissions can be set to (0.2, 0.5, 0.1, 0.2). When the task urgency is urgent, the priority is to reduce machine runtime. Computing time is the primary factor, and machine life, load overhead, and carbon emissions can be used as subsidiary factors. In this case, the weighting of computing time, machine life, load overhead, and carbon emissions can be set to (0.6, 0.3, 0.1, 0). When the task urgency is relatively relaxed, energy conservation and carbon emission reduction are prioritized. Carbon emissions are the primary factor, and computing time, machine life, and load overhead are used as subsidiary factors. In this case, the weighting of computing time, machine life, load overhead, and carbon emissions can be set to (0.1, 0.3, 0.1, 0.5). A target group of processing devices is determined from the multiple processing devices based on the weights of the aforementioned factors. For example, device A is a processing device with low carbon emissions; device B is a processing device with a short lifespan; device C is currently processing other tasks, has a heavy load, and is expensive to use; and device D is highly efficient. Based on information about changes in target task demand, the weights of the influencing factors in the third processing model are adjusted. Based on the weights of the influencing factors, processing devices that match the weights of the influencing factors are selected from the multiple processing devices, and the target group of processing devices is determined from the multiple processing devices.

[0128] In some embodiments, determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information includes:

[0129] determining a task level of the target task based on the task information;

[0130] determining a target configuration weight of target device information of a processing device based on the task level;

[0131] Obtaining score data of at least two processing device groups under the target configuration weight, wherein at least one of the type, quantity, and collocation combination of the processing devices in different processing device groups is different;

[0132] A target processing device group is determined from the at least two processing device groups based on the scoring data.

[0133] In the present application, the electronic device can set the task level of the target task according to the task information of the target task, and the task level can represent the urgency of the task. Thus, the calculation time, machine life, load overhead and carbon emission factor weight ratio of the required processing equipment are determined according to the urgency of the task. It can be understood that there can be multiple processing equipment groups that can perform the target task, and the scores of each processing equipment group can be calculated for the multiple processing equipment groups under the limitation of the calculation time, machine life, load overhead and carbon emission factor weight ratio. According to the ranking from high to low, the processing equipment group corresponding to the highest ranking score is used as the target processing equipment group.

[0134] For example, in the above embodiment, in the first task scenario, the task urgency is normal, and ensuring the longevity of the machine combination is prioritized. In this case, multiple configuration options for the processing device group are available: Option 1: 5 devices A and 5 devices B. Option 2: 7 devices A and 3 devices B. Option 3: 2 devices A and 8 devices B.

[0135] Among them, first obtain the scores of the computing time, machine life, load overhead, and carbon emission factors of the equipment in Solution 1. The scores can be obtained based on expert evaluation, as shown in Table 1.

[0136] Table 1 Scores of influencing factors

[0137] factor excellent better generally Poor Difference Calculation duration 4 2 1 0 0 Machine life 6 1 0 0 0 Load overhead 0 0 5 1 1 carbon emissions 2 2 1 1 1

[0138] Then normalize it to get the matrix R1.

[0139]

[0140] Taking the machine life of the processing equipment as the main factor, the target weight parameter A=(0.1, 0.3, 0.1, 0.5), and then based on the target weight parameter and matrix R1, through the fuzzy comprehensive evaluation algorithm,

[0141] B=A×R

[0142] b j ≤=max{(a i ×r ij )1≤i≤n}(j=1,2,…m)

[0143] Among them, b j is the comprehensive evaluation vector, r ij represents the factor weight, a i Indicates the importance of the factor in the evaluation.

[0144] Using the fuzzy comprehensive evaluation algorithm, the evaluation value for Option 1, B1, is obtained as (0.5, 0.2, 0.14, 0.14, 0.14). Normalized, it is B1 = (0.46, 0.18, 0.12, 0.12, 0.12). Finally, based on the pre-set score, for example, 10 points for excellent evaluation, 7 points for good evaluation, 5 points for average evaluation, 3 points for poor evaluation, and 1 point for bad evaluation, the final value of B1 is calculated as B1 = 0.46 × 10 + 0.18 × 7 + 0.12 × 5 + 0.12 × 3 + 0.12 × 1 = 6.94.

[0145] The same method is used to calculate the evaluation score B2 for the processing equipment group in Solution 2 and the evaluation score B3 for the processing equipment group in Solution 3. The scores of B1, B2, and B3 are ranked in descending order, and the processing equipment group with the highest score is selected as the target processing equipment group. It will be understood that if there are multiple solutions, an evaluation score is calculated for each solution, and then all evaluation scores are ranked in descending order. The processing equipment group with the highest evaluation score among these ranked scores is selected as the target processing equipment group.

[0146] Similarly, in the above embodiment, in the second task scenario, the task urgency is urgent, and reducing machine runtime is prioritized. In this case, the target weight parameter A = (0.6, 0.3, 0.1, 0). The processing equipment group solutions can be Solution 1, Solution 2, and Solution 3, or other solutions. In the second task scenario, with machine life as the primary factor, a fuzzy comprehensive evaluation algorithm is used to calculate the scores of B1, B2, and B3 for the second task scenario. The processing equipment group with the highest score is selected as the target processing equipment group.

[0147] In the above embodiment, in the third task scenario, the task has been determined to be completed ahead of schedule, and energy conservation and carbon emission reduction are prioritized. In this case, the target weight parameter A = (0.1, 0.3, 0.1, 0.5). Using carbon emissions as the primary factor, a fuzzy comprehensive evaluation algorithm is used to calculate the scores of B1, B2, and B3 for the third task scenario. The processing equipment group with the highest score is selected as the target processing equipment group.

[0148] In some embodiments, determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information includes at least one of the following:

[0149] inputting the task information and the device information into a third processing model deployed on the electronic device, so as to output a target processing device group determined from a plurality of processing devices using the third processing model;

[0150] The target processing devices are selected from the plurality of processing devices based on a matching relationship between the target task and the target processing device determined by the task information and the device information to form the target processing device group.

[0151] In the present application, a third processing model is provided in the electronic device, which can be a spiral detection multi-factor balance model. The spiral detection multi-factor balance model can analyze the task information and device information of the target task after receiving them, and calculate the score of the processing device group obtained based on the task information, thereby determining the evaluation score of each processing device group, and determining the processing device group with the highest evaluation score as the target processing device group.

[0152] In this application, the electronic device can also determine a matching relationship between a target task and a processing device based on the task information and device information. For example, if the target task is image processing, a processing device with image processing capabilities or a model with image processing functions is required. Based on the matching relationship, a target processing device is selected from multiple processing devices. There can be more than one target processing device, and more than one target processing device constitutes a target processing device group.

[0153] Exemplarily, the devices connected or capable of being connected to the electronic device are determined based on the device information, such as device A with a model training function, device B with an image processing function, device C with a text generation function, device D with a video generation function, and device E with a voice recognition function. If the task information is obtained, the function required for the target task to be processed is determined. For example, the target task is image recognition. According to the device information, it can be known that device B has an image processing function. Therefore, the target task is matched with device B to obtain a target processing device group. If the target task is a video composed of multiple images obtained after processing multiple images, it is determined based on the device information that device B has an image processing function and device D has a video generation function. Therefore, the target task is matched with device B and device D, and the combination of device B and device D is used as the target processing device group.

[0154] Alternatively, the electronic device stores a history book of the target task and user habit data, and device A among the processing devices has not only a model training function but also an image processing function; device B has an image processing function, but according to historical data, the user is accustomed to using device A for image processing, so the target task generated by the image is matched with device A, and device A is used as the target processing device.

[0155] The present application provides an electronic device including at least one processor and at least one processing model capable of running on the processor, wherein the processing model can be called by a target application to perform at least one of the following:

[0156] In response to obtaining the target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with the electronic device;

[0157] determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices;

[0158] The target processing device group can change dynamically as the execution requirements of the target task change.

[0159] In the present application, a connection can be established between an electronic device and a plurality of processing devices. When the electronic device receives a target task, it analyzes the target task and obtains the task information of the target task. And obtains the device information of the plurality of processing devices connected to the electronic device. Based on the task information of the target task obtained by analysis and the device information obtained, the target processing device group that can process the target task is determined. It is understandable that, depending on the target task, the target processing device group determined by the electronic device in the present application is different based on the task information and device information of the target task. If the execution requirements of the target task change, the target processing device group that can execute will change accordingly.

[0160] For example, during model training, multiple processing devices include device A, device B, and device C. Based on the task information of model training and the device information of device A, device B, and device C, it is determined that the device group consisting of device A and device B can perform the task of model training, and the target processing device group is determined to be the device group consisting of device A and device B.

[0161] The term "electronic device" in this application is intended to refer to 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 term "electronic device" may also refer to various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices.

[0162] The present application provides a task processing system, including an electronic device and multiple processing devices connected to the electronic device, wherein:

[0163] After the electronic device obtains the target task, the electronic device obtains device information of the plurality of processing devices based on the connection;

[0164] as well as,

[0165] determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices;

[0166] The target processing device group can change dynamically as the execution requirements of the target task change.

[0167] like Figure 3 As shown, the task processing system provided by the present application includes an electronic device 301, which is connected to a first processing device 302, a second processing device 303 and a third processing device 304. After obtaining the target task, the electronic device 301 obtains the device information of the first processing device 302, the second processing device 303 and the third processing device 304 based on the connection with the first processing device 302, the second processing device 303 and the third processing device 304, and then determines the target processing device group from the first processing device 302, the second processing device 303 and the third processing device 304 according to the task information of the target task and the device information of the first processing device 302, the second processing device 303 and the third processing device 304.

[0168] Exemplarily, electronic device 1 is a mobile phone, and the multiple processing devices are TV 1, TV 2 and a computer. The mobile phone can obtain the screen projection task input by the user. After receiving the screen projection task, it obtains the device information of TV 1, TV 2 and the computer, and selects the device that can project the screen as the target processing device. For example, TV 1 is in the power-on and idle state, TV 2 is in the power-on and processing other task state, and the computer is in the power-on and idle state. The mobile phone uses TV 1 and the computer as target processing devices and can project the screen to TV 1 or the computer.

[0169] like Figure 4 As shown, electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. Various programs and data required for the operation of device 800 can also be stored in RAM 803. Computing unit 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0170] Various components in device 800 are connected to I / O interface 805, including an input unit 806, such as a keyboard, mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0171] The computing unit 801 can be a variety of general-purpose and / or specialized processing components with processing and computing capabilities. Some examples of the computing unit 801 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 that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as the task processing method. For example, in some embodiments, the task processing method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the task processing method described above can be performed. Alternatively, in other embodiments, the computing unit 801 can be configured to perform the task processing method by any other appropriate means (e.g., by means of firmware).

[0172] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes 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.

[0173] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing 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 can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0174] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can 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 can 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.

[0175] 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).

[0176] The systems and techniques described herein can 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 having 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 can 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.

[0177] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0178] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0179] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the present disclosure, "plurality" means two or more, unless otherwise specifically defined.

[0180] The above description is merely a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A task processing method, comprising: In response to obtaining the target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with the electronic device; determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices; The target processing device group can change dynamically as the execution requirements of the target task change.

2. The method according to claim 1, further comprising: Determining demand change information of the execution demand of the target task based on the task information or target reference data; The configuration parameters of the target processing device group are updated based on the demand change information.

3. The method according to claim 2, wherein determining the requirement change information of the execution requirement of the target task based on the task information or target reference data comprises at least one of the following: Determining demand change information of the execution demand of the target task based on task information of executed tasks and / or tasks to be executed in the target task; Using a first processing model to generate and process task information of executed tasks and / or tasks to be executed in the target task to obtain the demand change information; Performing corresponding processing on the obtained target reference data using a second processing model to obtain the demand change information, wherein the target reference data includes target input data of the target user acting on the electronic device and / or operation change data of the processing device; Target reference data is obtained, and the demand change information is determined in a corresponding manner based on a source of the target reference data.

4. The method according to claim 3, wherein: Determining the demand change information of the execution demand of the target task based on the task information of the executed tasks and / or the tasks to be executed in the target task includes at least one of the following: Determining a task progress of the target task based on task information of executed tasks among the target tasks, and generating demand change information of an execution demand of the target task based on the task progress; generating demand change information of the execution demand of the target task based on at least one of the task type, task amount, and task priority of the task to be executed in the target task; The task progress represented by the executed tasks in the target task and at least one of the task type, task amount, and task priority of the task to be executed are input into the first processing model for generation processing to obtain the demand change information of the execution demand.

5. The method according to claim 3, wherein Determining the demand change information in a corresponding manner based on a source of the target reference data includes at least one of the following: In a case where the target reference data comes from first input data applied by a target user to an electronic device, determining the first input data as the demand change information, wherein the first input data is used to adjust an execution strategy of the target task, the execution strategy being related to configuration parameters of the target device group; In a case where the target reference data is derived from second input data applied by a target user to an electronic device, generating and processing the second input data using a second processing model to obtain the demand change information, wherein the second input data includes feedback data or evaluation data on execution results of executed tasks in the target task; In a case where the target reference data comes from operation change data of the processing equipment obtained by monitoring the target processing equipment group, the operation change data is processed using a second processing model to obtain the demand change information; When the target reference data comes from environmental change data of the environment in which the target processing device group is located and / or newly added tasks to be processed, the second processing model is used to generate and process the environmental change data and / or the tasks to be processed to obtain the demand change information.

6. The method according to claim 2, wherein updating the configuration parameters of the target processing device group based on the demand change information comprises at least one of the following: updating at least one of the configuration type, configuration quantity, and collocation combination of the processing devices in the target processing device group based on the demand change information; adjusting the operating parameters and / or the assigned tasks of at least one processing device in the target processing device group based on the demand change information; Adjust the target weight parameters of the third processing model based on the demand change information to update the configuration parameters of the target processing device group, wherein: The third processing model is a model for determining a target processing device group from among a plurality of processing devices.

7. The method according to claim 1, wherein determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information comprises: determining a task level of the target task based on the task information; determining a target configuration weight of target device information of a processing device based on the task level; Obtaining score data of at least two processing device groups under the target configuration weight, wherein at least one of the type, quantity, and collocation combination of the processing devices in different processing device groups is different; A target processing device group is determined from the at least two processing device groups based on the scoring data.

8. The method according to claim 1, wherein determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information comprises at least one of the following: inputting the task information and the device information into a third processing model deployed on the electronic device, so as to output a target processing device group determined from a plurality of processing devices using the third processing model; The target processing devices are selected from the plurality of processing devices based on a matching relationship between the target task and the target processing device determined by the task information and the device information to form the target processing device group.

9. An electronic device comprising at least one processor and at least one processing model capable of running on the processor, wherein the processing model can be called by a target application to perform at least one of the following: In response to obtaining the target task, obtaining device information of a plurality of processing devices, wherein the plurality of processing devices are devices that are connected to or capable of establishing a connection with the electronic device; determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices; in, The target processing device group can be dynamically changed as the execution requirements of the target task change.

10. A task processing system comprising an electronic device and a plurality of processing devices connected to the electronic device, wherein: After the electronic device obtains the target task, the electronic device obtains device information of the plurality of processing devices based on the connection; as well as, determining a target processing device group from the plurality of processing devices based on the task information of the target task and the device information, so as to execute the target task using the target processing device group, the target processing device group including at least one of the plurality of processing devices; The target processing device group can change dynamically as the execution requirements of the target task change.

Images