MpC + ScaLAPACK = efficient solving linear Algebra problems on heterogeneous networks

Abstract

The paper presents experience of using mpC for accelerating ScaLAPACK applications on heterogeneous networks of computers. The mpC is a language, specially designed for parallel programming for heterogeneous networks. It has facilities for distribution of participating processes over processors in accordance with performances of the latters. An mpC application carring out Cholesky factorization on a heterogeneous network of workstations is used to demonstrate that the heterogeneous process distribution has an essential advantage over the traditional homogeneous distribution. The application is implemented using calls to ScaLAPACK routines by means of the interface mpC - ScaLAPACK. © Springer-Verlag Berlin Heidelberg 1999.