Experimental Study of Six Different Parallel Matrix-Matrix Multiplication Applications for Heterogeneous Computational Clusters of Multicore Processors
Pedro Alonso, Ravi Reddy, Alexey Lastovetsky · 2009
In this document, we describe two strategies of distribution of computations that can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore Processors (HCoMs). These strategies are called Heterogeneous Process Distribution Strategy (HPS) and Heterogeneous Data Distribution Strategy (HDS). They are not novel and have already been researched thoroughly. However, the advent of multicores necessitates enhancements to them. We conduct experiments using six applications utilizing the various distribution strategies to perform parallel matrix-matrix multiplication (PMM) on a local HCoM. The first application calls ScaLAPACK PBLAS routine PDGEMM, which uses the traditional homogeneous strategy of distribution of computations. The second application is an MPI application, which utilizes HDS to perform the PMM. The application requires an input, which is the two-dimensional processor grid arrangement to use during the execution of the PMM. The third application is also an MPI application but that uses HPS to perform the PMM. The application requires two inputs, which are the number of threads to run per process and the two-dimensional process grid arrangement to use during the execution of the PMM. The fourth