Research on Performance Analysis Techniques for Parallel Program Optimization on Domestic CPU Architecture

With the increasing use of high-performance computing, users are turning to programs for concurrent execution enhance the speed and overall performance of large-scale programs. This trend is supported through the use of a portable messaging interface (MPI), communication can be facilitated in a convenient and efficient manner. We employ the MPI-based performance analysis tool mpiP for evaluating program performance, focusing on a matrix multiplication model through numerous targeted experiments with a fixed number of processors. Expanding the scale of the experimental use case matrix; fixing the scale of the matrix and scaling up the number of processors in order to clearly analyze the program performance and improve the performance analysis of mpiP. At the same time, the execution sequence detection and visualization functions are added in the improvement process. The mpiP report makes it easier for users to perform global performance analysis on the program. This not only improves the overall performance analysis efficiency, it also facilitates tracking the progress of individual processes throughout the program's execution.