Performance analysis of parallel supernodal sparse LU factorization
Conference
·
OSTI ID:822182
- LBNL Library
We investigate performance characteristics for the LU factorization of large matrices with various sparsity patterns. We consider supernodal right-looking parallel factorization on a bi-dimensional grid of processors, making use of static pivoting. We develop a performance model and we validate it using the implementation in SuperLU-DIST, the real matrices and the IBM Power3 machine at NERSC. We use this model to obtain performance bounds on parallel computers, to perform scalability analysis and to identify performance bottlenecks. We also discuss the role of load balance and data distribution in this approach.
- Research Organization:
- Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
- Sponsoring Organization:
- USDOE Director. Office of Science. Computational and Technology Research (US)
- DOE Contract Number:
- AC03-76SF00098
- OSTI ID:
- 822182
- Report Number(s):
- LBNL--54497
- Country of Publication:
- United States
- Language:
- English
Similar Records
A new scheduling algorithm for parallel sparse LU factorization with static pivoting
SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
SparseLU, A Novel Algorithm and Math Library for Sparse LU Factorization
Conference
·
Tue Aug 20 00:00:00 EDT 2002
·
OSTI ID:822956
SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
Journal Article
·
Tue Mar 26 23:00:00 EST 2002
· ACM Transaction on Mathematical Software
·
OSTI ID:836786
SparseLU, A Novel Algorithm and Math Library for Sparse LU Factorization
Conference
·
Tue Nov 01 00:00:00 EDT 2022
·
OSTI ID:2000278