Design and Performance Issues of Cholesky and LU Solvers Using UPCBLAS

Partitioned Global Address Space (PGAS) languages offer programmers a shared memory view that increases their productivity and allow locality exploitation to obtain good performance on current large-scale distributed memory systems. UPCBLAS is a parallel numerical library for dense matrix computations using the PGAS Unified Parallel C (UPC) language. The interface of this library exploits the characteristics of the PGAS memory model and thus it is easier to use than MPI-based libraries. This paper addresses the implementation of solvers of systems of equations through Cholesky and LU factorizations in UPC using UPCBLAS. The developed codes are experimentally evaluated and compared to the MPI versions using ScaLAPACK. Parallel solvers of equations are present in many parallel numerical applications and they have been traditionally developed in MPI. This work shows that UPCBLAS can be considered as a good alternative to the MPI-based libraries for increasing the productivity of numerical application developers.