基于申威1600的3级BLAS GEMM函数优化

BLAS是当前科学计算领域重要的底层支持数学库之一，其中的3级BLAS函数应用最为广泛.本文基于国产申威1600平台，提出了一种基础线性代数库BLAS的三级函数通用矩阵乘GEMM的高性能实现方法.在单核上，使用乘加指令、循环展开、软件流水线指令重排、SIMD向量化运算、寄存器分块技术等与平台架构相关的技术手段，实现汇编级手工优化；在多核上，提出了适用于该平台的多线程加速方案.实验结果显示，在单核串行性能测试中，与知名开源数学库GotoBLAS相比，我们实现了平均4.72倍的加速效果；在多核并行扩展测试中，4线程版的性能则平均达到了单线程版性能的3.02倍.

Optimization of BLAS Level 3 Functions on SW1600

BLAS is one of the most important basic underlying math library for scientific computing,in which the level 3 BLAS functions are most widely used.In this paper,we provide a high-performance method to implement Level 3 BLAS functions based on domestic Sunway 1600 platform.To make it clear,we take GEMM as an example.For the implementation on single-core,we apply many tuning techniques related to the specific platform,such as multiply-add instructions,loop unrolling,software pipelining and instruction rearrangement,SIMD operations,and register blocking to push up the performance.For the multi-core implementation,we propose an efficient multi-threaded method.Compared with GotoBLAS,one of the famous open-source BLAS,the experiments show that our serial single-threaded method achieves a speedup of 4.72.What''s more,the average speedup of 4-threaded execution towards the single-threaded one can also reach 3.02.