Affiliations: Department of Computer Science, University of
Tennessee at Knoxville, 107 Ayres Hall, Knoxville, TN 37996-1301; e-mail:
{choi,dongarra,sost,petitet,rwhaley}@cs.utk.edu | Mathematical Sciences Section, Oak Ridge National
Laboratory, P.O. Box 2008, Bldg. 6012, Oak Ridge, TN 37831-6367; e-mail:
walker@rios2.epm.oral.gov
Abstract: This article discusses the core factorization routines included in
the ScaLAPACK library. These routines allow the factorization and solution of a
dense system of linear equations via LU, QR, and Cholesky. They are implemented
using a block cyclic data distribution, and are built using de facto standard
kernels for matrix and vector operations (BLAS and its parallel counterpart
PBLAS) and message passing communication (BLACS). In implementing the ScaLAPACK
routines, a major objective was to parallelize the corresponding sequential
LAPACK using the BLAS, BLACS, and PBLAS as building blocks, leading to
straightforward parallel implementations without a significant loss in
performance. We present the details of the implementation of the ScaLAPACK
factorization routines, as well as performance and scalability results on the
Intel iPSC/860, Intel Touchstone Delta, and Intel Paragon System.
