ecrc/ksvd: The KAUST SVD (KSVD) is a high performance software framework for computing a dense SVD on distributed-memory manycore systems.

Type
Software
Authors
Sukkari, Dalal cc
Ltaief, Hatem cc
Schmidr, Drew
Gonzalez F, Eduardo
KAUST Department
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Extreme Computing Research Center
Date
2017-11-13
Permanent link to this record
http://hdl.handle.net/10754/668119

Metadata
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Abstract
The KAUST SVD (KSVD) is a high performance software framework for computing a dense SVD on distributed-memory manycore systems.
Publisher
Github
Additional Links
https://github.com/ecrc/ksvd
Relations
Is Supplement To:
  • [Dissertation]
    Sukkari, D. (2019). High Performance Polar Decomposition on Manycore Systems and its application to Symmetric Eigensolvers and the Singular Value Decomposition. KAUST Research Repository. https://doi.org/10.25781/KAUST-R20B1. DOI: 10.25781/KAUST-R20B1 Handle: 10754/652466
  • [Article]
    Sukkari, D., Ltaief, H., Esposito, A., & Keyes, D. (2019). A QDWH-based SVD Software Framework on Distributed-memory Manycore Systems. ACM Transactions on Mathematical Software, 45(2), 1–21. doi:10.1145/3309548. DOI: 10.1145/3309548 Handle: 10754/626212
Collections
Applied Mathematics and Computational Science Program; Extreme Computing Research Center; Software; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division