CN114820269A - Data processing system, method, apparatus, device and storage medium - Google Patents

Abstract

The application provides a data processing system, a method, a device, equipment and a storage medium. The data processing system includes a first device and a second device connected wirelessly or by wire. The first device is used for obtaining a data processing task comprising an image rendering task or an artificial intelligence calculation task and sending the data processing task to the second device, and the second device executes corresponding image rendering operation or artificial intelligence calculation operation according to the received data processing task and obtains a corresponding image rendering result or an artificial intelligence calculation result, so that the second device sends the generated image rendering result or the artificial intelligence calculation result to the first device. Because the first device can obtain the required data processing result by using the second device, the first device is not required to be configured with hardware with higher data processing capacity, and the hardware requirement and cost for the first device are reduced.

Description

Data processing system, method, apparatus, device and storage medium

technical field

The present application relates to the technical field of data processing, and in particular, to a data processing system, method, apparatus, device, and storage medium.

Background technique

At present, in application scenarios such as work and entertainment, people usually prefer to use lightweight devices, such as laptops, tablets, VR/AR glasses and other devices. However, the data processing performance of such devices is usually not high enough to support the powerful computing power required for some businesses. For example, in 3D image rendering scenarios, it is usually difficult for lightweight devices to quickly complete 3D image rendering tasks.

In order to improve the data processing performance of a portable device as much as possible, it is usually necessary to integrate as much hardware as possible on the device to strengthen its data processing performance. However, limited by the requirements of the size and weight of the portable device, the performance enhancement effect brought by the integrated hardware is not significant, and the cost is relatively high.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present application provide a data processing system to improve the data processing performance of the device. The present application also provides corresponding methods, apparatuses, devices, computer-readable storage media, and computer program products.

In the first aspect, an embodiment of the present application provides a data processing system, the system includes a first device and a second device, and the connection between the first device and the second device may be a wireless connection or a wired connection. . The first device is used to obtain a data processing task, and the data processing task specifically includes an image rendering task or an artificial intelligence computing task. Then, the first device can send the data processing task to the second device, and the second device can perform a corresponding image rendering operation or artificial intelligence computing operation according to the received data processing task. Specifically, when the received data processing task When the image rendering operation is performed, the second device performs the image rendering operation and obtains the corresponding image rendering result; and when the received data processing task is an artificial intelligence computing operation, the second device performs the artificial intelligence computing operation and obtains The corresponding artificial intelligence calculation results. Next, the second device sends the generated image rendering result or artificial intelligence calculation result to the first device, so that the first device receives the required image rendering result or artificial intelligence calculation result.

Since the first device can obtain the required data processing result by using the second device, there is no need to require the first device to configure hardware with higher data processing capability, which reduces hardware requirements and costs for the first device. In this way, not only can the first device be made lighter and consume less power, but also, when the data processing capability of the second device is high, the computing power requirement required by the first device to achieve the service can also be guaranteed.

In a possible implementation manner, the first device is further configured to perform a corresponding image rendering operation or an artificial intelligence computing operation according to the data processing task when the first device is disconnected from the second device. In this way, when the first device cannot use the second device to process the task, it can use its own data processing capability to process the task, thereby avoiding that the data processing task cannot be processed when the first device is disconnected from the second device. implement.

In a possible implementation manner, the first device may also present a device selection interface, where the device selection interface is used to receive a user's selection operation for a device that performs an image rendering operation or an artificial intelligence computing operation, that is, the user selects a device using the first When a device performs the operation, the second device is used to perform the operation, or another device connected to the first device is used to perform the operation. When the selection operation performed by the user indicates that the device performing the image rendering operation or the artificial intelligence computing operation is the second device, the first device may intercept the data processing task generated by the first device. In this way, the first device can determine the device to perform the above operation based on the user's selection, which increases the selectivity for the user and improves the user experience.

In a second aspect, an embodiment of the present application further provides a data processing method, the data processing method can be applied to a first device, and the first device can be connected to a second device, and during the processing, the first device can obtain A data processing task, the data processing task includes an image rendering task or an artificial intelligence computing task, and the data processing task is sent to the second device, and then the first device receives the image rendering result or the artificial intelligence computing result sent by the second device, the The image rendering result or the artificial intelligence calculation result is obtained by performing a corresponding image rendering operation or an artificial intelligence calculation operation based on the data processing task.

After the first device sends the data processing task to the second device, the second device can be used to obtain the required data processing results, and there is no need to require the first device to configure hardware with higher data processing capabilities, which reduces the complexity of the first device. Hardware requirements and costs. In this way, not only can the first device be made lighter and consume less power, but also, when the data processing capability of the second device is high, the computing power requirement required by the first device to achieve the service can also be guaranteed.

In a possible implementation manner, the first device may also perform a corresponding image rendering operation or an artificial intelligence computing operation according to the data processing task when the first device is disconnected from the second device. In this way, when the first device cannot use the second device to process the task, it can use its own data processing capability to process the task, thereby avoiding that the data processing task cannot be processed when the first device is disconnected from the second device. implement.

In a possible implementation manner, the data processing performance of the first device performing the image rendering operation or the artificial intelligence computing operation is higher than the data processing performance of the first device performing the image rendering operation or the artificial intelligence operation In this way, the first device can use the second device with higher data processing performance to perform data processing tasks, which can improve the efficiency of the first device in obtaining image rendering results or artificial intelligence calculation results.

In a possible implementation manner, when the first device acquires the data processing task, it may specifically present a device selection interface, where the device selection interface is used to receive a user's selection operation for a device that performs an image rendering operation or an artificial intelligence computing operation , that is, the user selects whether to use the first device to perform the operation, or to use the second device to perform the operation, or to use other devices connected to the first device to perform the operation. When the selection operation performed by the user indicates that the device performing the image rendering operation or the artificial intelligence computing operation is the second device, the first device may intercept the data processing task generated by the first device. In this way, the first device can determine the device to perform the above operation based on the user's selection, which increases the selectivity for the user and improves the user experience.

In a possible implementation manner, the first device may also present the image rendering result or the artificial intelligence calculation result in the target area in the display interface. In this way, it is not only convenient for the user to view the data processing result, but also when presenting the image rendering result. , the image rendering result may also be presented to the user on the display interface together with the unrendered image, wherein the unrendered image may be presented in other areas of the display interface except the target area.

In a third aspect, the present application provides a data processing apparatus, which can be applied to a first device, and the first device is connected to a second device, and the apparatus is used to implement the second aspect or any possible implementation of the second aspect Each module of the data processing method executed by the first device in the mode.

In a fourth aspect, the present application provides a computing device, where the computing device includes a processor and a memory. The processor and the memory communicate with each other. The processor is configured to execute the instructions stored in the memory, so that the computing device executes the data processing method executed by the first device in the second aspect or any implementation manner of the second aspect.

In a fifth aspect, the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, when the computer-readable storage medium runs on a computing device, the computing device performs the second aspect or any of the second aspects. A data processing method described in an implementation manner.

In a sixth aspect, the present application provides a computer program product containing instructions, which, when run on a computing device, enables the computing device to execute the data processing method described in the second aspect or any implementation manner of the second aspect .

On the basis of the implementation manners provided by the above aspects, the present application may further combine to provide more implementation manners.

Description of drawings

FIG. 1 is a schematic diagram of the architecture of an exemplary data processing system of the present application;

2 is a schematic diagram of an exemplary application selection interface provided by an embodiment of the present application;

3 is a schematic diagram of an exemplary display interface provided by an embodiment of the present application;

4 is a schematic diagram of an exemplary device selection interface provided by an embodiment of the present application;

5 is a schematic flowchart of a data processing method provided by an embodiment of the present application;

6 is a schematic diagram of the architecture of another exemplary data processing system provided by an embodiment of the present application;

FIG. 7 is a schematic flowchart of another data processing method provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of the architecture of still another exemplary data processing system provided by an embodiment of the present application;

FIG. 9 is a schematic structural diagram of a data processing apparatus provided by an embodiment of the present application;

FIG. 10 is a schematic diagram of a hardware structure of a computing device according to an embodiment of the present application.

Detailed ways

The solutions in the embodiments provided in this application will be described below with reference to the accompanying drawings in this application.

The terms "first", "second" and the like in the description and claims of the present application and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, and this is only a distinguishing manner adopted when describing objects with the same attributes in the embodiments of the present application.

Portable devices, such as VR glasses, have certain requirements in terms of size, weight, etc. Therefore, the hardware on the device has limited data processing performance, and it is usually difficult to support the portable device to achieve the higher requirements for some services. Great computing power. Even if the portable device has integrated as much hardware as possible to enhance the data processing performance of the device, it is difficult to achieve a significant enhancement effect; at the same time, integrating hardware on the portable device will increase the cost of the portable device. Including hardware cost, design cost, etc.

In other possible solutions, the portable device can also be connected to the cloud, and the powerful computing power of the cloud can be used to improve the data processing performance of the portable device. However, in this cloud processing method, the applications that implement the business run in the cloud, and the portable device acts as a display device that presents the cloud processing results to the user. Therefore, when the portable device is removed from the cloud, the portable device cannot continue to perform business.

Based on this, an embodiment of the present application provides a data processing system, where the data processing system at least includes a portable device and a local computing device. The local computing device refers to a device that is wired or wirelessly connected to the first device. When a portable device implements business, it can send data processing tasks such as image rendering or artificial intelligence computing generated by itself to the local computing device, so that the local computing device can perform the corresponding image rendering operation or artificial intelligence computing operation, and will get The image rendering results or artificial intelligence calculation results are fed back to the portable device, so that the portable device can use the local computing device to obtain the required data processing results, without requiring the portable device to configure hardware with higher data processing capabilities, reducing the need for Hardware requirements and costs for portable devices. In this way, not only can the portable device be made lighter and consume less power, but also when the data processing capability of the local computing device is high, the portable device can also meet the computing power requirements required by the business.

Further, the local computing device is only responsible for performing corresponding image rendering operations or artificial intelligence computing operations, while the application programs that implement services run on the portable device and do not depend on the local computing device. If the connection between them is disconnected, the portable device can continue to realize the business based on its own data processing capability, and there is usually no problem that the business cannot continue to be realized.

Next, various non-limiting embodiments of object recognition are described in detail.

As shown in FIG. 1 , it is a schematic structural diagram of an exemplary data processing system provided by an embodiment of the present application. As shown in FIG. 1 , the data processing system 100 includes a first device 101 and a second device 102 . The first device 101 and the second device 102 may be connected by wire, such as through a USB data cable; or, the first device 101 and the second device 102 may be connected wirelessly, such as through simple service discovery Protocol (Simple Service Discovery Protocol, SSDP), Network Service Definition (Network Service Definition, NSD) protocol, Bluetooth and other methods to achieve wireless connection and so on.

As an example, the first device 101 may include a device discovery module 1011 , and the device discovery module may be used to find and connect to the second device 102 . For example, the device discovery module 1011 can broadcast a device discovery message in the local area network based on the SSDP protocol, so as to detect one or more devices in the local area network that can be connected to the first device 101, so that the first device 101 can find one or more devices from the discovered one or more devices. One of the devices determines to connect with the second device 102, and can further send a corresponding connection request to the second device 102. When the first device 101 receives the connection success notification information fed back by the second device 102, the first device 101 It is determined that the communication connection with the second device 102 is successfully established. Certainly, the specific implementation of establishing the communication connection between the first device and the second device 102 by the device discovery module 1011 is not limited to the above example.

Exemplarily, the first device 101 can be, for example, the above-mentioned portable device, and the second device 102 can be, for example, the above-mentioned local computing device. Alternatively, the first device 101 and the second device 102 may also be other possible devices. For example, in other possible scenarios, the size or weight of the first device 101 may also be other devices that exceed the requirements of portable devices. In addition, the data processing capability of the second device 102 when performing data processing operations (eg, the above-mentioned image rendering operations or artificial intelligence computing operations) may be higher than the data processing capability of the first device 101 when performing the data processing operations. In other possible implementation manners, the data processing capability of the second device 102 may also be lower than the data processing capability of the first device 101, or the data processing capabilities of the two devices are the same. In this embodiment, the specific implementation of the first device 101 and the second device 102 and the data processing capabilities of the first device 101 and the second device 102 are not limited.

The first device 101 may carry an application program, and the application program may implement corresponding services when running, such as a 3D image rendering service, an artificial intelligence (artificial intelligence, AI) computing service, and the like. In the process of implementing the service, the first device 101 may generate corresponding data processing tasks to instruct the first device 101 to use the hardware configured by itself (that is, the data processing capability it has itself) to perform the tasks required for implementing the service. Data processing operations. Specifically, the data processing task may be an image rendering task. In this case, the image rendering task may instruct the first device 101 to perform a corresponding image rendering operation, such as rendering a 2D image into a 3D image; or, the data processing task may It is an artificial intelligence computing task. In this case, the artificial intelligence computing task may instruct the first device 101 to perform a corresponding artificial intelligence computing operation, such as an intelligent operation required to realize human-computer interaction such as voice dialogue.

In a possible implementation manner, the first device 101 may further include an application control module 1012 . The user can trigger the application control module 1012 on the first device 101 to start an application, such as an application for rendering a 3D image. Alternatively, the application control module 1012 may present the application selection interface shown in FIG. 2 to the user on the first device 101, and the presented application selection interface includes shortcuts of multiple different applications (in FIG. The shortcut of the application is used as an exemplary illustration), the shortcut of each application can be, for example, the icon of the application, etc., so that the application control module 1012 can determine and start the application corresponding to the shortcut according to the user's click operation on the shortcut, For example, when the user clicks the shortcut (icon) of the application 5 in FIG. 2 , the application control module 1012 can determine and start the application 5 . During the application startup process, the application control module 1012 can monitor whether the application is successfully started, such as capturing the startup status of the application through the Hook technology.

After using the application control module 1012 to capture the application startup, the first device 101 can send the data processing task generated when the application is running to the second device 102, so that the second device can perform corresponding data processing according to the data processing task. The operation may specifically be the above-mentioned image rendering operation or artificial intelligence computing operation.

In an exemplary implementation, the first device 101 may include a redirection module 1013 . After detecting that the application is successfully started, the application control module 1012 can notify the redirection module 1013 to redirect the data processing task. At this time, the redirection module 1013 can intercept the data processing task generated by the first device 101, and redirect the data processing task to the second device 102 through the connection between the first device 101 and the second device 102, so as to The second device 102 is instructed to perform a data processing operation. In this embodiment, the redirection module 1013 may be configured to be responsible for the redirection of data processing tasks corresponding to multiple services in a unified manner; or, it may also be used in the first device 101 for data processing tasks corresponding to different services using different The redirection module realizes redirection. For example, for the 3D image rendering service, the redirection module A in the first device 101 can redirect the data processing task of the service to the second device 102, while for the AI computing service, the redirection module A can redirect the data processing task of the service to the second device 102. The data processing task of the service is redirected to the second device 102 and so on by the redirection module B in the first device 101 . In practical application, the data processing task intercepted by the redirection module 1013 may specifically be an instruction for processing corresponding data, etc., and redirects the intercepted instruction to the second device 102 .

The second device 102 may perform corresponding data processing operations using its own data processing capabilities according to the received data processing tasks. In this embodiment, the data processing operation performed by the second device 102 may specifically be an image rendering operation or an AI computing operation or the like. For different services on the first device 101, the second device 102 may perform different data processing operations, and this embodiment does not limit the specific operations performed by the second device 102.

In an example, when performing a data processing operation, the second device 102 may parse out service data and an operation instruction from the received data processing task, and perform a data processing operation corresponding to the operation instruction on the service data. For example, in an AI computing scenario, the second device 102 may parse input data participating in AI computing from the data processing task, and perform a corresponding AI computing process based on the input data. In other examples, the data processing task may only contain an indication of the operation type, while the service data may be sent by the first device 101 to the second device 102 alone. For example, in a 3D image rendering scenario, after sending the data processing task to the second device 102, the first device 101 can continue to send multiple frames of 2D images to the second device, so that the second device 102 can send the second device 102 according to the data processing task. The indicated rendering operation renders subsequently received multiple frames of 2D images into 3D images.

After performing a corresponding data processing operation according to the data processing task, the second device 102 may generate a corresponding data processing result, which may specifically be an image rendering result or an artificial intelligence calculation result. Then, the second device 102 can feed back the generated data processing result to the first device 101, so that the first device 101 can present the received data processing result to the user, for example, in the target area in the corresponding display interface The rendered 3D image or AI calculation result is presented to the user or the like. Wherein, in the 3D image rendering scene, the first device 101 can send the 2D image in the target area shown in the left side of FIG. 3 on the display interface to the second device 102 for image rendering, so that the first device 101 is displaying the image to the user. When presenting the display interface, the 2D image on the display interface can be fused with the rendered 3D image sent by the second device 102, and specifically, the 3D image can be controlled to be displayed in the target area, and the 3D image on the display interface can be controlled to be displayed. Other areas are still displayed as 2D images, as shown on the right side of Figure 3. In other examples, the result presented by the first device 101 on the display interface may also be an artificial intelligence calculation result, or simultaneously include an artificial intelligence calculation result and an image rendering result, and the like.

In this embodiment, for multiple different services, the first device 101 can redirect all data processing tasks corresponding to the services to the second device 102 by default, so as to use the second device 102 to perform data processing required to realize the services operate. In other possible implementation manners, the first device 101 may also determine whether to implement the service by means of the second device 102 based on the user's selection.

For example, before notifying the redirection module 1013 that the application is successfully started, the application control module 1012 may present the device selection interface as shown in FIG. 4 to the user, and present “Do you want to use hardware acceleration for the currently started application?” on the device selection interface. (or "Whether to use other devices to assist computing?") and other prompt information, so as to prompt the user to choose whether to use the first device 101 alone to implement the service, or choose to implement the service with the help of the second device 102 . When the application control module 1012 determines that the device performing the data processing operation is the second device 102 according to the selection operation performed by the user, the application control module 1012 can notify the redirection module 1013 that the application is successfully started, so that the redirection module 1013 will intercept the data processing task and redirect it to the second device 102 for execution; and when the application control module 1012 determines according to the selection operation that the device performing the data processing operation is the first device 101, the application control module 1012 may not notify the redirection module 1013 that the application is successfully started , and instructs the first device 101 to use its own data processing capability to perform data processing tasks, so that the first device 101 can independently implement services.

In addition, the present application also provides a data processing method, which can be applied to the data processing system 100 shown in FIG. 1 , and of course can also be applied to other applicable data processing systems. Hereinafter, the data processing method will be described in detail with reference to specific application scenarios and accompanying drawings.

Referring to FIG. 5 , it is a schematic flowchart of a data processing method in an embodiment of the present application. The method can be applied to the data processing system 600 as shown in FIG. 6 and used to realize the 3D image rendering service. Wherein, the first device 101 and the second device 102 in the data processing system 600 are connected wirelessly (of course, in other embodiments, it may also be a wired connection, etc.). The data processing method shown in FIG. 5 may specifically include:

S501: The device discovery module 1011 discovers the second device 102.

In this embodiment, the device discovery module 1011 on the first device 101 may pre-discover the surrounding local devices that can be connected to it. For example, it may discover local devices that can establish a communication connection with the first device 101 through the SSDP protocol, the NSD protocol or other methods. equipment.

Exemplarily, when the device discovery module 1011 discovers one or more local devices, it can automatically select one of the local devices as the second device 102 . For example, the device discovery module 1011 may select the local device with the smallest load as the second device 102 according to the load of each local device. Of course, in other embodiments, the device discovery module 1011 may also present relevant information of each discovered local device (for example, device identification, device function, etc.) to the user, so as to determine the local device according to the user's selection operation Which local device is used as the second device 102 . In this embodiment, the specific implementation manner in which the application control module 1012 determines the second device 102 is not limited.

S502: The device discovery module 1011 establishes a communication connection between the first device 101 and the second device 102.

Exemplarily, the second device 102 may include a device connection module 1021 . When establishing the communication connection between the first device 101 and the second device 102 , the device discovery module 1011 may specifically send a connection request to the device connection module 1021 in the second device 102 . The device connection module 1021 may establish a connection with the first device 101 based on the connection request, and feed back notification information of successful connection to the device discovery module 1011 .

Of course, if the establishment of the communication connection between the first device 101 and the second device 102 fails, the device connection module 1021 can feed back notification information of the connection failure to the device discovery module 1011, so that the application control module can re-select other local devices as the present implementation. The second device 102 in the example. Further, the device connection module 1021 can also collect the reasons for the connection failure, and send the connection failure reasons together with the notification information to the device discovery module 1011, so that the application control module 1012 can present the connection failure reasons to the user.

S503: The application control module 1012 starts the application on the first device 1011 according to the trigger operation of the user.

S504: The application control module 1012 controls the application to start successfully.

In this embodiment, the user can trigger the application control module 1012 on the first device 101 to successfully start the application. In other possible embodiments, the user can start the application through the shortcut of the application. At this time, the application control module 1012 can monitor the startup status of the application. For example, it can monitor whether the application is successfully started through the Hook technology. For the specific implementation, please refer to The description of the relevant parts of the foregoing embodiments will not be repeated here.

S505: The application control module 1012 selects to use the second device 102 to perform the data processing operation, that is, determines to use hardware acceleration.

In this embodiment, in the process of implementing the service, the first device 101 may determine whether to implement the service independently or to implement the 3D image rendering service by means of the second device 102 . In some examples, the first device 101 may select a specific service, such as the aforementioned 3D image rendering service, to be implemented by the second device 102 by default, that is, use the second device 102 to perform a 3D image rendering operation required to implement the service. In other examples, the user can select a device that implements the service, so that the application control module 1012 can determine whether the device performing the 3D image rendering operation is the first device 101 or the second device 102 according to the user's selection operation.

S506: The application control module 1012 instructs the redirection module 1013 to redirect the data processing task generated by the first device 101, where the data processing task is used for instructing to generate a 3D image.

The first device 101 may generate a data processing task according to a user's requirement for using an application. For example, when a user needs to view a 3D image in the process of using an application, the first device 101 (specifically, an application on the first device 101 ) may generate a data processing task for rendering a 3D image. The step of generating the data processing task by the first device 101 (not shown in FIG. 5 ) may be located before any of steps S501 to S505 , which is not limited in this embodiment.

S507: The redirection module 1013 intercepts the data processing task.

Exemplarily, the redirection module 1013 may, for example, intercept the data processing task by calling interface functions such as OpenGL and DirectX, and the specific implementation for implementing instruction interception is not limited in this embodiment.

S508: The redirection module 1013 redirects the data processing task to the image rendering module 1022 in the second device 102, where the data processing task carries the 2D image to be rendered.

In this embodiment, the 2D image to be rendered is carried in the data processing task as an example for illustration. In practical applications, the 2D image may also be sent by the first device 101 to the second device 102 alone. This is not limited.

S509: The image rendering module 1022 renders the 2D image into a 3D image according to the data processing task.

In practical application, the data processing task may include multiple frames of 2D images, and the image rendering module 1022 may render some frame images of the multiple frames of 2D images. For example, assuming that the image rendering module 1022 parses out 20 2D images from the data processing task, which are numbered 1 to 20, the image rendering module 1022 can select and number 1, 4, 7, 10, 13, and 16 at equal intervals, respectively. , 19 These 7 2D images are rendered, and the corresponding 7 3D images are obtained. Of course, in other embodiments, the image rendering module 1022 may also perform 3D image rendering for all 2D images, etc., which is not limited in this embodiment.

S510: The encoding module 1023 captures the 3D image rendered by the image rendering module 1022.

In practical applications, since a 3D image has a frame rate during display, such as displaying 30 frames of 3D images per second, etc., when capturing a 3D image, the encoding module 1023 can also capture a 3D image according to the display frame rate of the 3D image, such as The encoding module 1023 can capture 30 frames of 3D images and the like in 1 second.

S511: The encoding module 1023 encodes the captured 3D image to form a video stream.

As an example, the encoding module 1023 may encode the captured 3D image into a compressed code stream, such as an H.264 video code stream of a video. Of course, it may also be a code stream encoded in other formats, which is not limited in this embodiment.

S512: The encoding module 1023 sends the encoded video stream to the decoding module 1014 in the first device 101 through the connection between the first device 101 and the second device 102.

S513: The decoding module 1014 decodes the received video stream, and displays the decoded 3D image in the target area on the display interface.

In practical application, the decoding module 1014 can display the 3D image obtained by decoding and the 2D image generated by the first device 101 on the display interface. Specifically, each frame of the 3D image can be displayed in sequence in the target area of the display interface, and the 2D image can be displayed on the display interface. The 2D image is displayed in the non-target area of the interface, so that the display interface can present the effect of merging the 2D image and the 3D image to the user.

In the above-mentioned embodiment, the first device 101 and the second device 102 are used to complete the 3D image rendering task in an exemplary illustration. In other possible application scenarios, the relationship between the first device 101 and the second device 102 is It may be to collaboratively implement the AI computing service on the first device 101 .

Referring to FIG. 7 , it is a schematic flowchart of a data processing method in an embodiment of the present application. The method can be applied to the data processing system 800 as shown in FIG. 8 and used to realize the 3D image rendering service. The first device 101 and the second device 102 in the data processing system 800 may be connected wirelessly. The data processing method shown in FIG. 7 may specifically include:

S701: The device discovery module 1011 discovers the second device 102.

S702: The device discovery module 1011 establishes a communication connection between the first device 101 and the second device 102.

S703: The application control module 1012 starts the application on the first device 1011 according to the trigger operation of the user.

S704: The application control module 1012 controls the application to start successfully.

S705: The application control module 1012 selects to use the second device 102 to perform a data processing operation.

S706: The application control module 1012 notifies the redirection module 1013 to redirect the data processing task generated by the first device 101, where the data processing task is used to instruct the execution of AI computing.

It should be noted that, in this embodiment, the specific implementations of steps S701 to S706 are similar to the specific implementations of steps S501 to S506 in the foregoing embodiments, and the relevant descriptions of the foregoing embodiments may be referred to, and will not be repeated here. .

S707: The redirection module 1013 intercepts the data processing task.

As some implementation examples, the redirection module 1013 can call functions such as TensorFlow and Pytorch in the AI development and operation framework to implement the intercepted data processing task; or, the redirection module 1013 can implement the intercepted data processing task through underlying acceleration functions such as NVidia cuDNN.

S708: The redirecting module 1013 redirects the data processing task to the AI computing module 1024 in the second device 102, where the data processing task carries the input data of the AI computing.

In this embodiment, the input data that participates in the AI calculation is carried in the data processing task as an example for illustration. In practical applications, the input data may also be sent by the first device 101 to the second device 102 alone. In this embodiment This is not limited.

S709: The AI calculation module 1024 performs a corresponding AI calculation process according to the data processing task, and generates an AI calculation result.

S710: The AI calculation module 1024 feeds back the generated AI calculation result to the redirection module 1013.

S711 : The redirection module 1013 forwards the received AI calculation result to the application on the first device 101 .

The data processing methods provided by the embodiments of the present application are described above with reference to FIGS. 1 to 8 . Next, the apparatuses and computing devices for implementing the data processing methods provided by the embodiments of the present application are introduced with reference to the accompanying drawings.

Figure 9 provides a data processing apparatus. As shown in FIG. 9 , the data processing apparatus 900 can be applied to a first device, and the first device is wired or wirelessly connected to the second device. The apparatus 900 specifically includes:

an acquisition module 901, configured to acquire a data processing task, where the data processing task includes an image rendering task or an artificial intelligence computing task;

The communication module 902 is configured to send the data processing task to the second device, and receive an image rendering result or an artificial intelligence calculation result sent by the second device, where the image rendering result or the artificial intelligence calculation result is It is obtained by performing a corresponding image rendering operation or an artificial intelligence computing operation based on the data processing task.

In a possible implementation manner, the apparatus 900 further includes:

The executing module 903 is configured to execute a corresponding image rendering operation or an artificial intelligence computing operation according to the data processing task when the first device is disconnected from the second device.

In a possible implementation manner, the data processing performance of the second device is higher than the data processing performance of the first device.

In a possible implementation manner, the obtaining module 901 is specifically configured to:

presenting a device selection interface, where the device selection interface is configured to receive a user's device selection operation for performing the image rendering operation or the artificial intelligence computing operation;

When the selection operation indicates that the device performing the image rendering operation or the artificial intelligence computing operation is the second device, the data processing task generated by the first device is intercepted.

In a possible implementation manner, the apparatus 900 further includes:

The presentation module 904 is configured to present the image rendering result or the artificial intelligence calculation result in the target area in the display interface.

The data processing apparatus 900 according to the embodiments of the present application may correspond to executing the methods described in the embodiments of the present application, and the above-mentioned and other operations and/or functions of the various modules of the data processing apparatus 900 are respectively to implement the respective methods in the foregoing embodiments The corresponding process, for the sake of brevity, will not be repeated here.

Figure 10 provides a computing device. As shown in FIG. 10 , the computing device 1000 may be specifically configured to implement the functions performed by the first device 101 in the embodiments shown in the foregoing FIGS. 5 and 7 .

Computing device 1000 includes bus 1001 , processor 1002 and memory 1003 . A bus 1001 communicates between the processor 1002 and the memory 1003 .

The bus 1001 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus or the like. The bus can be divided into address bus, data bus, control bus and so on. For ease of presentation, only one thick line is used in FIG. 10, but it does not mean that there is only one bus or one type of bus.

The processor 1002 may be a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP), etc. any one or more of the devices.

The memory 1003 may include volatile memory, such as random access memory (RAM). The memory 1003 may also include non-volatile memory (non-volatile memory), such as read-only memory (ROM), flash memory, hard drive drive (HDD) or solid state drive (SSD) ).

Executable program codes are stored in the memory 1003 , and the processor 1002 executes the executable program codes to execute the aforementioned data processing method executed by the first device 101 .

Embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium may be any available medium that a computing device can store, or a data storage device such as a data center that contains one or more available media. The usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVDs), or semiconductor media (eg, solid state drives), and the like. The computer-readable storage medium includes instructions that instruct the computing device to execute the data processing method executed by the first device 101 described above.

The embodiments of the present application also provide a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on the computing device, all or part of the processes or functions described in the embodiments of the present application are generated.

The computer instructions may be stored in or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted over a wire from a website site, computer or data center. (eg coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (eg infrared, wireless, microwave, etc.) to another website site, computer or data center.

The computer program product can be a software installation package, which can be downloaded and executed on a computing device when any of the aforementioned object recognition methods needs to be used.

The descriptions of the processes or structures corresponding to each of the above-mentioned drawings have their own emphasis, and for the parts that are not described in detail in a certain process or structure, reference may be made to the related descriptions of other processes or structures.

Claims (15)

1. A data processing system, said system comprising a first device and a second device, said first device being connected to said second device;

the first device is used for obtaining a data processing task, wherein the data processing task comprises an image rendering task or an artificial intelligence calculation task, sending the data processing task to the second device, and receiving an image rendering result or an artificial intelligence calculation result sent by the second device;

and the second equipment is used for executing corresponding image rendering operation or artificial intelligence calculation operation according to the received data processing task and sending the obtained image rendering result or artificial intelligence calculation result to the first equipment.

2. The system of claim 1, wherein the first device is further configured to:

and when the first equipment is disconnected from the second equipment, executing corresponding image rendering operation or artificial intelligence calculation operation according to the data processing task.

3. The system according to claim 1 or 2, characterized in that the first device is specifically configured to:

presenting a device selection interface for receiving a user selection operation for a device performing the image rendering operation or the artificial intelligence computing operation;

and when the selection operation indicates that the equipment for executing the image rendering operation or the artificial intelligence computing operation is the second equipment, intercepting a data processing task generated by the first equipment.

4. A data processing method is applied to a first device, the first device is connected with a second device, and the method comprises the following steps:

acquiring a data processing task, wherein the data processing task comprises an image rendering task or an artificial intelligence computing task;

sending the data processing task to the second device;

and receiving an image rendering result or an artificial intelligence calculation result sent by the second device, wherein the image rendering result or the artificial intelligence calculation result is obtained by executing corresponding image rendering operation or artificial intelligence calculation operation based on the data processing task.

5. The method of claim 4, further comprising:

and when the first equipment is disconnected from the second equipment, executing corresponding image rendering operation or artificial intelligence calculation operation according to the data processing task.

6. The method of claim 4 or 5, wherein the second device performs the image rendering operation or the artificial intelligence computing operation with a higher data processing performance than the first device performs the image rendering operation or the artificial intelligence computing operation.

7. The method of any of claims 4 to 6, wherein the obtaining a data processing task comprises:

presenting a device selection interface for receiving a device selection operation by a user for performing the image rendering operation or the artificial intelligence computing operation;

and when the selection operation indicates that the equipment for executing the image rendering operation or the artificial intelligence computing operation is the second equipment, intercepting a data processing task generated by the first equipment.

8. The method according to any one of claims 4 to 7, further comprising:

and presenting the image rendering result or the artificial intelligence calculation result in a target area in a display interface.

9. A data processing apparatus, wherein the data processing apparatus is applied to a first device, the first device is connected to a second device, and the data processing apparatus comprises:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring data processing tasks, and the data processing tasks comprise image rendering tasks or artificial intelligence calculation tasks;

and the communication module is used for sending the data processing task to the second equipment and receiving an image rendering result or an artificial intelligence calculation result sent by the second equipment, wherein the image rendering result or the artificial intelligence calculation result is obtained by executing corresponding image rendering operation or artificial intelligence calculation operation based on the data processing task.

10. The apparatus of claim 9, further comprising:

and the execution module is used for executing corresponding image rendering operation or artificial intelligence calculation operation according to the data processing task when the first equipment is disconnected from the second equipment.

11. The apparatus according to claim 9 or 10, wherein the second device has a higher data processing performance than the first device.

12. The apparatus according to any one of claims 9 to 11, wherein the obtaining module is specifically configured to:

presenting a device selection interface for receiving a device selection operation by a user for performing the image rendering operation or the artificial intelligence computing operation;

and when the selection operation indicates that the equipment for executing the image rendering operation or the artificial intelligence computing operation is the second equipment, intercepting a data processing task generated by the first equipment.

13. The apparatus of any one of claims 9 to 12, further comprising:

and the presentation module is used for presenting the image rendering result or the artificial intelligence calculation result in a target area in a display interface.

14. A computing device comprising a processor, a memory;

the processor is to execute instructions stored in the memory to cause the computing device to perform the method of any of claims 4 to 8.

15. A computer-readable storage medium comprising instructions that, when executed on a computing device, cause the computing device to perform the method of any of claims 4 to 8.

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