Method for distributing tasks by general purpose graphic processing unit in multi-task concurrent execution manner

Abstract

The invention discloses a method for distributing tasks by a general purpose graphic processing unit in a multi-task concurrent execution manner. The method comprises the following steps: firstly classifying kernel functions through a thread block distribution engine method; carrying out classified counting on the kernel functions to obtain the number of thread blocks of the kernel functions which are respectively distributed to a streaming processor; and distributing the thread blocks with different kernel function corresponding numbers into a same streaming multiprocessor so as to achieve the aims of improving the resource utilization rate of each streaming multiprocessor in the general purpose graphic processing unit and enhancing the system performance and the energy efficiency ratio. A level-1 data cache bypass method can be further utilized; and according to the method, a dynamic method is used for determining the thread block of which kernel function is bypassed, and then bypassing is carried out according to the number of the bypassed thread blocks of the kernel functions, so as to achieve the aims of lightening the pressure of the level-1 data cache and further improving the performance.

Description

technical field [0001] The invention belongs to the technical field of high-performance computing, and relates to a multi-task concurrent execution method in high-performance computing, in particular to a task distribution method for a general-purpose graphics processing unit (GPGPU) multi-task concurrent execution. Background technique [0002] General-purpose graphics processing unit (GPGPU) is a processor that utilizes the characteristics of many-core structure, multi-threading and high memory access bandwidth of graphics processors to handle high-performance computing tasks such as biological computing, image processing and physical simulation. In modern computing, computing tasks have an urgent need for high performance and high throughput, so that general-purpose graphics processors are widely used in the computing field and play an increasingly important role. Moreover, with the development of cloud computing and the popularization of computing terminals, more and mor...

AI Technical Summary

Problems solved by technology

This method is a coarse-grained concurrency technology. Although it can balance the utilization of streaming multiprocessors and off-chip storage resources, the low utilization of computing resources inside a streaming multiprocessor is still a very serious problem.

[0007] In 2014, Lee et al. from the Korea Advanced Institute of Science and Technology (KAIST) proposed a hybrid concurrent kernel function execution scheme (Published on: High Performance Computer Architecture (HPCA), 2014IEEE20thInternational Symposium on , Pages260-271)

However, this scheme does not specifically deal with the scheduling problem of different kernel function thread blocks in the stream multiprocessor, nor does it propose an optimization scheme for level-1 data cache pollution

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