http://www.netlib.org/scalapack/index.html ScaLAPACK <abstract> The ScaLAPACK software library, scheduled for completion by the end of 1994, will extend the LAPACK library to run scalably on MIMD, distributed memory, concurrent computers. For such machines, the memory hierarchy includes the off-processor memory of other processors, in addition to the hierarchy of registers, cache, and local memory on each processor. Like LAPACK, the ScaLAPACK routines are based on block-partitioned algorithms in order to minimize the frequency of data movement between different levels of the memory hierarchy. The fundamental building blocks of the ScaLAPACK library are distributed memory versions of the Level 2 and Level 3 BLAS, and a set of Basic Linear Algebra Communication Subprograms (BLACS) for communication tasks that arise frequently in parallel linear algebra computations. In the ScaLAPACK routines, all interprocessor communication occurs within the distributed BLAS and the BLACS, so the source code of the top software layer of ScaLAPACK looks very similar to that of LAPACK. Six ScaLAPACK routines are currently available from NETLIB -- parallel LU, QR, and Cholesky factorization routines, and parallel Hessenberg (HRD), tridiagonal (BRD), and bidiagonal (BRD) reduction routines. The ScaLAPACK routines are based on PB-BLAS (Parallel Blocked Basic Linear Algebra Subprograms), which is a distributed memory version of the Level 2 and Level 3 BLAS. ScaLAPACK is currently available only for double precision real data, but will be implemented in the near future for other data types. <contact>scalapack@cs.utk.edu <keywords>parallel numerical library; linear algebra; distributed memory multiprocessor; MIMD machine <category>numerical-linalg </urc>