Method and apparatus for scheduling GPU to perform batch operation

A technology of batch and calculation results, applied in the field of GPU parallel computing, can solve problems such as increasing program complexity and difficulty, and achieve the effect of improving memory access performance

Inactive Publication Date: 2016-01-06
成都卫士通信息产业股份有限公司
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  • Application Information

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Problems solved by technology

Even if multiple threads are used to call the GPU, each thread assigns the task to the GPU to only schedule one GPUCORE to participate in the calculation. Compared with batching the tasks to the GPU and letting each core of the GPU participate in the calculation, the performance gap may be different. thousand times more than the latter
[0005] Our applications based on the CPU architecture usually use multi-process or multi-thread to process multiple tasks. After receiving a task, it will c

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  • Method and apparatus for scheduling GPU to perform batch operation

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[0028] All the features disclosed in this specification, or all disclosed methods or steps in the process, except for mutually exclusive features and / or steps, can be combined in any manner.

[0029] Any feature disclosed in this specification (including any appended claims, abstract and drawings), unless specifically stated, can be replaced by other equivalent or equivalent alternative features. That is, unless otherwise stated, each feature is just one example of a series of equivalent or similar features.

[0030] The implementation steps of the present invention are as follows:

[0031] 1. Use the synchronous mode API:

[0032] a) Deploy GPU;

[0033] b) Deploy and run the GPU scheduling module;

[0034] c) The application module calls the synchronous mode API to perform calculation tasks.

[0035] 2. Use asynchronous mode API:

[0036] a) Deploy GPU;

[0037] b) Deploy and run the GPU scheduling module;

[0038] Transform the application module, call the asynchronous mode API, and proc...

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Abstract

The present invention relates to the field of GPU parallel computing, in particular to a method and an apparatus for scheduling a GPU to perform batch operation. Aimed at the problems in the prior art, the present invention provides the method and the apparatus for scheduling the GPU to perform the batch operation. According to the method and the apparatus provided by the present invention, a separate GPU scheduling module is designed and coordinates with the GPU to perform calculation task processing together with an API application module so as to sufficiently exert the operational capability of the GPU; the API application module sends an operation task to the GPU scheduling module and the GPU scheduling module stores calculation tasks received within a cycle in a cache; and when the GPU completes the calculation tasks in the last batch, the GPU scheduling module submits the cached calculation tasks to the GPU in batches and then the API application module completes the subsequent operations of the calculation tasks in a synchronous mode or an asynchronous mode.

Description

technical field [0001] The invention relates to the field of GPU parallel computing, in particular to a method and device for scheduling GPU to perform batch computing. Background technique [0002] A GPU (Graphics Processing Unit, graphics processing unit) can be understood as a programmable graphics card, which is used for processing graphics images in a computer. After development in recent years, GPU is not limited to graphics and image processing, but has also been applied to the field of large-scale parallel computing. Using GPU parallel computing technology may improve the performance of algorithms several times. [0003] A single GPU usually has hundreds or thousands of COREs (core computing units), far exceeding the number of CPU COREs. GPUs are very suitable for performing intensive computing tasks that can be highly parallelized. Compared with CPUs at the same price, GPUs use The number of cores used can be hundreds of times higher than that of the CPU, and using...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F9/48
Inventor 吴庆国
Owner 成都卫士通信息产业股份有限公司
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