ScaLAPACK
──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
top
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.cite-ref-1[1]cite-ref-2[2]cite-ref-3[3]
As of version 2.0, the code base directly includes PBLAS and BLACS and has dropped support for PVM.
After two decades of operation, a new library was created to replace ScaLAPACK, which was not suitable for modern accelerated architectures. Slate is written in C++ and was designed primarily to serve as a dense linear algebra library to the United States Department of Energy and to the high-performance computing community at large.cite-ref-4[4]cite-ref-5[5]
Contents
• Examples
──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Examples
• Programming with Big Data in R fully utilizes ScaLAPACK and two-dimensional block cyclic decomposition for Big Data statistical analysis which is an extension to R.
References
cite-note-11. ↑ citerefj-dongarra-and-d-walkerJ. Dongarra and D. Walker. "The Design of Linear Algebra Libraries for High Performance Computers". {{cite journal}}: Cite journal requires |journal= (help)
cite-note-33. ↑ "2d block-cyclic data layout".
cite-note-44. ↑ "SLATE". icl.utk.edu. Retrieved 2024-02-02.
cite-note-55. ↑ citerefgateskurzakchararayarkhan2019Gates, Mark; Kurzak, Jakub; Charara, Ali; YarKhan, Asim; Dongarra, Jack (2019-11-17). "SLATE: Design of a modern distributed and accelerated linear algebra library". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. SC '19. New York, NY, USA: Association for Computing Machinery. pp. 1–18. doi:10.1145/3295500.3356223. ISBN 978-1-4503-6229-0.
External links