ACM DL

Mathematical Software (TOMS)

Menu

Search Issue
enter search term and/or author name

Archive


ACM Transactions on Mathematical Software (TOMS), Volume 34 Issue 2, March 2008

PyTrilinos: High-performance distributed-memory solvers for Python
Marzio Sala, W. F. Spotz, M. A. Heroux
Article No.: 7
DOI: 10.1145/1326548.1326549

PyTrilinos is a collection of Python modules that are useful for serial and parallel scientific computing. This collection contains modules that cover serial and parallel dense linear algebra, serial and parallel sparse linear algebra, direct and...

Parallel unsymmetric-pattern multifrontal sparse LU with column preordering
Haim Avron, Gil Shklarski, Sivan Toledo
Article No.: 8
DOI: 10.1145/1326548.1326550

We present a new parallel sparse LU factorization algorithm and code. The algorithm uses a column-preordering partial-pivoting unsymmetric-pattern multifrontal approach. Our baseline sequential algorithm is based on UMFPACK 4, but is somewhat...

On the design of interfaces to sparse direct solvers
Marzio Sala, Kendall S. Stanley, Michael A. Heroux
Article No.: 9
DOI: 10.1145/1326548.1326551

We discuss the design of general, flexible, consistent, reusable, and efficient interfaces to software libraries for the direct solution of systems of linear equations on both serial and distributed memory architectures. We introduce a set of...

Scalable parallelization of FLAME code via the workqueuing model
Field G. Van Zee, Paolo Bientinesi, Tze Meng Low, Robert A. van de Geijn
Article No.: 10
DOI: 10.1145/1326548.1326552

We discuss the OpenMP parallelization of linear algebra algorithms that are coded using the Formal Linear Algebra Methods Environment (FLAME) API. This API expresses algorithms at a higher level of abstraction, avoids the use loop and array...

Algorithm 873: LSTRS: MATLAB software for large-scale trust-region subproblems and regularization
Marielba Rojas, Sandra A. Santos, Danny C. Sorensen
Article No.: 11
DOI: 10.1145/1326548.1326553

A MATLAB 6.0 implementation of the LSTRS method is presented. LSTRS was described in Rojas et al. [2000]. LSTRS is designed for large-scale quadratic problems with one norm constraint. The method is based on a reformulation of the...