PYTRILINOS: High-performance distributed-memory solvers for python

0Citations
Citations of this article
22Readers
Mendeley users who have this article in their library.
Get full text

Abstract

PYTRILINOS is a collection of Python modules targeting serial and parallel sparse linear algebra, direct and iterative linear solution techniques, domain decomposition and multilevel preconditioners, nonlinear solvers and continuation algorithms. Also included are a variety of related utility functions and classes, including distributed I/O, coloring algorithms and matrix generation. PYTRILINOS vector objects are integrated with the popular NumPy module, gathering together a variety of high-level distributed computing operations with serial vector operations. PYTRILINOS uses a hybrid development approach, with a front-end in Python, and a back-end, computational engine in compiled libraries. As such, PYTRILINOS makes it easy to take advantage of both the flexibility and ease of use of Python, and the efficiency of the underlying C++, C and FORTRAN numerical kernels. The presented numerical results show that, for many important problem classes, the overhead required by the Python interpreter is negligible. © Springer-Verlag Berlin Heidelberg 2007.

Cite

CITATION STYLE

APA

Sala, M., Spotz, W. F., & Heroux, M. A. (2007). PYTRILINOS: High-performance distributed-memory solvers for python. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, pp. 966–975). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_114

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free