Algorithm Implementation and Optimization of Symmetric Matrix Eigenvalue Solution for FT-M6678
Currently,there is no implementation related to the symmetric matrix eigenvalue solution on China's autonomous and controllable FT-M6678 platform,and the existing mathematical calculation library on this platform cannot satisfy the requirements for solving similar problems.This study focuses on the domestic FT-M6678 processor,implements and optimizes the algorithm of the symmetric matrix eigenvalue solution,SYEV,and improves the linear algebra calculation library of the FT-M6678 platform.First,by analyzing the implementation process and running hotspots of the SYEV algorithm,compile,memory access,and vector parallel optimizations are performed based on the FT-M6678 platform.Compilation optimization refers to guiding the compiler to optimize programs based on different compilation options to achieve acceleration effects;memory access optimization includes cache optimization and allocation optimization of data and program segments,accelerating the efficiency of matrix data access;and vector parallelization optimization includes loop unrolling and Single Instruction Multiple Data(SIMD)instruction parallel optimization adapted to the FT-M6678 platform,which improves the computational efficiency of programs.Verification and performance tests of the implemented and optimized algorithms are performed using the FT-M6678 platform.The accuracy of the algorithms passes the test of official Linear Algebra PACKage(LAPACK)test set,and the optimization acceleration effect of the algorithm on the FT-M6678 platform can reach 58.346 times,which can improve the speed by 2.053 times compared with the TMS320C6678 platform.
国家科技期刊平台
NSTL
万方数据
维普
