Triangular matrix multiplication vectorization method of vector processor

Abstract

The invention discloses a triangular matrix multiplication vectorization method of a vector processor. The triangular matrix multiplication vectorization method of the vector processor comprises the steps that (1) triangular matrix elements in a multiplicand triangular matrix T are stored continuously by row; (2) a multiplier matrix B is divided into a plurality of sub-matrixes Bi by row according to the number of vector processing units of the vector processor and the number of MAC parts of the vector processing units; (3) the sub-matrixes Bi are multiplied by the multiplicand triangular matrix T in sequence and then the results are stored on storage positions of the original sub-matrixes Bi; (4) the sub-matrixes Bi of the multiplier matrix are traversed and then the fact that whether sub-matrixes Bi which are not multiplied by the multiplicand triangular matrix exist is judged, the I is updated according to the formula i=i+1 and the steps are repeated from the step (3) if sub-matrixes Bi which are not multiplied by the multiplicand triangular matrix exist, and step (5) is executed if sub-matrixes Bi which are not multiplied by the multiplicand triangular matrix do not exist; (5) triangular matrix multiplication is accomplished. The triangular matrix multiplication vectorization method of the vector processor has the advantages that the principle is simple, operation is easy and convenient, and the calculation efficiency of the vector processor can be fully performed.

Description

technical field [0001] The invention mainly relates to the field of triangular matrix multiplication calculation, in particular to a vector processor-oriented triangular matrix multiplication vectorization method. Background technique [0002] Basic Linear Algebra Subprograms (BLAS) is a core mathematical library widely referenced in various scientific calculations and a core component of many mathematical software. At present, BLAS is widely used in scientific and engineering calculations such as physics, electronic engineering, biology, economics, and computing science. Among them, the two function libraries of triangular matrix-matrix multiplication and triangular matrix solve are one of the most frequently called function libraries. Since the transpose and inverse of a triangular matrix are still triangular matrices, these two types of function libraries can be attributed to the triangular matrix multiplication calculation: C=TB, where T is the upper triangular matrix o...

AI Technical Summary

Problems solved by technology

Compared with ordinary matrices, half of the matrix elements of triangular matrices are 0, so applying ordinary matrix multiplication in computing and storage cannot effectively improve the computing performance of triangular matrices

Moreover, the calculation on the vector processor-oriented platform, on the one hand, because the triangular matrix is ​​not a square matrix like an ordinary matrix, it is difficult to achieve regular data alignment and cannot balance the calculation load of each processing unit; on the other hand, the vector data access unit The supported vector data Load / Store generally only supports vector data reading by row, but does not support vector data reading by column, and cannot support support such as the patent "matrix multiplication with reduced bandwidth requirements" (application number: 200710097456.4) The column-wise access matrix elements of

How to efficiently realize the vectorized calculation of triangular matrix multiplication on the vector processor, so as to fully utilize the computing power of the vector processor is a technical difficulty that needs to be solved at present, and there is no vectorized method of triangular matrix multiplication for vector processors in the open literature

Images