基于申威1621处理器的BLAS一级函数优化

BLAS (Basic Linear Algebra Subprograms)是一个基本线性代数操作的数学函数标准, 该库函数分为三个级别, 每个级别提供了向量与向量(1级)、向量与矩阵(2级)、向量与向量(三级)之间的基本运算. 本文研究了在申威1621处理器上BLAS一级函数的优化方案, 以函数AXPY为例, 充分利用平台的架构特点对其进行性能调优,设计了自动的线程分配方案. 实验结果显示优化过后的BLAS一级函数AXPY相对于GotoBLAS参考实现版本的单核和多核加速比分别高达4.36和9.50, 对于每种优化方式均得到了一定的性能提升.

Optimization of BLAS Level 1 Functions on SW1621 Processor

The Basic Linear Algebra Subprogram (BLAS) is a mathematical function standard for basic linear algebra operations. The library function is divided into three levels in which basic operations between vector and vector (level 1), vector and matrix (level 2), and vector and vector (level 3) are offered. In this paper, we study the optimization scheme of BLAS level1 functions on SW1621 processor. With the function AXPY as an example, the architectural characteristics of the platform are fully used to optimize its performance, and an automatic thread allocation scheme is designed. The experimental results show that compared with the reference implementation version of GotoBLAS, the optimized BLAS level1 function, AXPY, has a high single-core acceleration ratio of 4.36 and a multi-core one of 9.50 respectively. Every optimization scheme can improve the performance.