Parallelization and performance comparison of the conjugate gradient equation solver on multicore Cell and Xeon computers

Abstract

SUMMARYMulticore accelerators are used today to supplement traditional superscalar processors in massively parallel computer nodes with extra floating-point computation power. This paper presents our parallelization and performance enhancement and evaluation of the conjugate gradient (CG) linear equation solver with enhanced matrix multiplication on the Cell Broadband Engine accelerator. The paper also compares the CG performance results on the Cell and two CG implementations on a computer with two quadcore Xeon processors, one with OpenMP and the other with OpenMPI. We also report the enhancements made on the CG code and performance analysis of CG on single and dual Cell Broadband Engine packages with 8 and 16 synergistic processing elements and on Xeon for heptadiagonal matrices, in particular to matrix multiplication and synchronization. We also report the communication and computation time breakdowns and the floating point operations per second ratio. Our parallel CG solver is shown to scale well with data size, grid dimensionality, and number of cores.