@inproceedings{956019ba38f345fd813456e1b0f98032,
title = "WSSMP: A high-performance serial and parallel symmetric sparse linear solver",
abstract = "The Watson Symmetric Sparse Matrix Package, WSSMP, is a high-performance, robust, and easy to use software package for solving large sparse symmetric systems of linear equations. It can can be used as a serial package, or in a shared-memory multiprocessor environment, or as a scalable parallel solver in a message-passing environment, where each node can either be a uniprocessor or a shared-memory multiprocessor. WSSMP uses scalable parallel multifrontal algorithms for sparse symmetric factorization and triangular solves. Sparse symmetric factorization in WSSMP has been clocked at up to 210 MFLOPS on an RS6000/590, 500 MFLOPS on an RS6000/397 and in excess of 20 GFLOPS on a 64-node SP with RS6000/397 nodes. This paper gives an overview of the algorithms, implementation aspects, performance results, and the user interface of WSSMP.",
author = "Anshul Gupta and Mahesh Joshi and Vipin Kumar",
year = "1998",
doi = "10.1007/bfb0095336",
language = "English (US)",
isbn = "3540654143",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "182--194",
editor = "Bo Kagstrom and Erik Elmroth and Jack Dongarra and Jerzy Wasniewski",
booktitle = "Applied Parallel Computing",
note = "4th International Workshop on Applied Parallel Computing, PARA 1998 ; Conference date: 14-06-1998 Through 17-06-1998",
}