A subset of LAPACK routines redesigned for heterogenous computing

Edit Package scalapack

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.

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Filename Size Changed
_multibuild 0000000332 332 Bytes
scalapack-2.1.0.tgz 0005307441 5.06 MB
scalapack.changes 0000008168 7.98 KB
scalapack.spec 0000019286 18.8 KB
Revision 20 (latest revision is 26)
Dominique Leuenberger's avatar Dominique Leuenberger (dimstar_suse) accepted request 815395 from Egbert Eich's avatar Egbert Eich (eeich) (revision 20)
- Add compiler flag -fallow-argument-mismatch to allow build with
  gcc10. (forwarded request 815394 from eeich)
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