Error-controllable hybrid precision operator automatic optimization method

An optimization method and error technology, applied in the field of compilers, can solve the problems such as the quantization acceleration method of matrix multiplication operator, and achieve the effect of improving development efficiency and efficiency

Pending Publication Date: 2022-03-22
SUN YAT SEN UNIV
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Problems solved by technology

[0002] The effectiveness of deep learning in image processing and natural language processing tasks has led to the development of more and more applications. Existing deep learning compilers and hardware for mixed-precision computing are difficult to be used by non-neural network programs to improve matrix correlation. The computational efficiency of the multiplication operator, and there is currently no automatic, user-controllable error matrix multiplication operator quantitative acceleration method under a general program

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  • Error-controllable hybrid precision operator automatic optimization method
  • Error-controllable hybrid precision operator automatic optimization method
  • Error-controllable hybrid precision operator automatic optimization method

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Embodiment Construction

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. For the step numbers in the following embodiments, it is only set for the convenience of illustration and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art sexual adjustment.

[0041] refer to figure 1 , the present invention provides a method for automatic optimization of mixed precision operators with controllable errors, the method comprising the following steps:

[0042] S0, obtain the source code;

[0043] S1, the first optimization, based on the source code, under the given input, optimize the general matrix multiplication function through the ID conversion method, and record the running order of the general matrix multiplication function and its corresponding dimensions, and obtain ...

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Abstract

The invention discloses an error-controllable hybrid precision operator automatic optimization method, which comprises the following steps of: first optimization: under given input, optimizing a general matrix multiplication function through an ID (Identity) conversion method, and recording an operation sequence and a corresponding dimension of the general matrix multiplication function; second optimization: according to an optimized general matrix multiplication GEMM function ID list and a general matrix multiplication function sequence list, transmitting the input of each non-optimized general matrix multiplication calling function to a preset fast matrix multiplication function of different parameter combinations, and carrying out performance timing and error calculation; and third optimization: analyzing the obtained data, converting a single-precision matrix multiplication algorithm into a mixed-precision matrix multiplication operator, and outputting an optimized code. By using the method, the hybrid precision GEMM operator can help to improve the performance in a more complex and wider high-performance computing program. The method can be widely applied to the field of compilers.

Description

technical field [0001] The invention relates to the field of compilers, in particular to an error-controllable automatic optimization method for mixed-precision operators. Background technique [0002] The effectiveness of deep learning in image processing and natural language processing tasks has led to the development of more and more applications. Existing deep learning compilers and hardware for mixed-precision computing are difficult to be used by non-neural network programs to improve matrix correlation. The computational efficiency of the multiplication operator, and there is no automatic, user-controllable error quantization acceleration method for the matrix multiplication operator under the general program. Contents of the invention [0003] In order to solve the above-mentioned technical problems, the object of the present invention is to provide an error-controllable automatic optimization method for mixed-precision operators, to construct a set of automatic co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/41G06F8/72G06F17/16
CPCG06F8/4441G06F8/72G06F17/16
Inventor 莫泽威张献伟葛天傲
Owner SUN YAT SEN UNIV
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