LU Parallel Decomposition Optimization Algorithm Based on Kunpeng Processor

Scalable linear algebra PACKage(ScaLAPACK) is a parallel computing package suitable for MIMD(multiple instruction,multiple data) parallel computers with distributed storage.It is widely used in parallel application program development based on linear algebra operation.However,during the LU decomposition process,the routines in the ScaLAPACK library are not communication optimal and do not take full advantage of the current parallel architecture.To solve the above problems,a parallel LU factorization optimization algorithm(PLF) based on Kunpeng processor is proposed to achieve load balancing and adapt to domestic Kunpeng environment.PLF processes the data of different partitions of different processes differently.PLF allocates part of the data of each process to the root process for calculation.After the calculation is completed,the root process spreads the data back to each sub-process,which helps to fully utilize CPU resources and achieve load balancing.Tests are performed on single-node Intel 9320R processors and Kunpeng 920 processors.Intel MKL(Math Kernel Library) is used on the Intel platform,and PLF algorithm is used on the Kunpeng platform.After comparing the performance of solving equations of different scales on two platforms,it is found that the performance of solving equations on Kunpeng platform has a significant advantage compared with Intel platform.In the case of NUMA process and single thread,the optimized computing efficiency reaches 4.35% on a small scale on average,which is 215% higher than Intel's 1.38%.The average size of the medium scale reaches 4.24%,compared with 1.86% of Intel platform,an increase of 118%.The large-scale average reaches 4.24%,compared to Intel's 1.99%,an increase of 113%.