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.
CITATION STYLE
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
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