Performance Evaluation and Optimization of Operating System for Domestic Supercomputer

Supercomputers play a crucial role in supporting scientific computing applications.During these five years,our country is developing post-exascale domestic supercomputers.As one of the core components of supercomputers,the operating system's overhead will impact the performance of the supercomputer system.Therefore,the evaluation of the OS is one of the important subjects in supercomputer research.Among existing domestic OSs,openEuler offers high performance and compatibility on systems equipped with Kunpeng processors.However,openEuler has not been extensively applied to supercomputers.Therefore,it is necessary to evaluate its performance on supercomputers,and optimize the existing performance bottlenecks.Our work can be divided into two parts.1)We evaluate the compatibility of openEuler and its performance when running HPC applications.CentOS is used as a reference for comparison.The evaluation results show that when running non-communication-intensive applications,the performance of openEuler is comparable to CentOS.However,when using OpenMPI for collective communication operations such as Allreduce,the performance on openEuler decreases by up to 76.83%.Additionally,under thousand-core scale,the parallel efficiency of communication-intensive applications on openEuler decreases by up to 23.01%.2)Based on the performance issues with MPI collective communication identified during the evaluation process,we propose a performance modeling and optimization method.This method relies on the Hockney model of point-to-point communication to model the performance of various collective communication algorithm implementations.It predicts communication time under different numbers of processes and message sizes,enabling the selection of suitable collective communication algorithm implementations.Utilizing the MCA interface of OpenMPI,this method allows for dynamic adjustment of algorithm implementations at runtime.After optimization,the perfor-mance of HPC applications on openEuler has been significantly improved,with a maximum reduction in running time of 26%.