Package libscalapack: Information

The ScaLAPACK (or Scalable LAPACK) library includes a subset of LAPACK routines
redesigned for distributed memory MIMD parallel computers. It is currently
written in a Single-Program-Multiple-Data style using explicit message passing
for interprocessor communication. It assumes matrices are laid out in a
two-dimensional block cyclic decomposition.

ScaLAPACK is designed for heterogeneous computing and is portable on any
computer that supports MPI or PVM.

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. (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.) The fundamental building
blocks of the ScaLAPACK library are distributed memory versions (PBLAS) of the
Level 1, 2 and 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 PBLAS and the BLACS. One of the design goals of
ScaLAPACK was to have the ScaLAPACK routines resemble their LAPACK equivalents
as much as possible.

If You need man pages, install libscalapack-manpages.

Package libscalapack: Information

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