Lis (linear algebra library)

Lis (linear algebra library)
Stable release 1.5.65 / March 19, 2016 (2016-03-19)
Development status Active
Operating system Cross-platform
Available in C, Fortran
Type Software library
License New BSD License
Website www.ssisc.org/lis/

Lis (Library of Iterative Solvers for linear systems, pronounced [lis]) is a scalable parallel software library for solving linear equations and eigenvalue problems that arise in the numerical solution of partial differential equations using iterative methods.[1][2][3]

Features

Lis provides facilities for:

Example

A C program to solve the linear equation Ax=b is written as follows:

#include <stdio.h>
#include "lis_config.h"
#include "lis.h"

LIS_INT main(LIS_INT argc, char* argv[])
{
  LIS_MATRIX  A;
  LIS_VECTOR  b, x;
  LIS_SOLVER  solver;
  LIS_INT     iter;
  double      time;

  lis_initialize(&argc, &argv);

  lis_matrix_create(LIS_COMM_WORLD, &A);
  lis_vector_create(LIS_COMM_WORLD, &b);
  lis_vector_create(LIS_COMM_WORLD, &x);

  lis_input_matrix(A, argv[1]);
  lis_input_vector(b, argv[2]);
  lis_vector_duplicate(A, &x);

  lis_solver_create(&solver);
  lis_solver_set_optionC(solver);
  lis_solve(A, b, x, solver);

  lis_solver_get_iter(solver, &iter);
  lis_solver_get_time(solver, &time);
  printf("number of iterations = %d\n", iter);
  printf("elapsed time = %e\n", time);

  lis_output_vector(x, LIS_FMT_MM, argv[3]);

  lis_solver_destroy(solver);
  lis_matrix_destroy(A);
  lis_vector_destroy(b);
  lis_vector_destroy(x);

  lis_finalize();

  return 0;
}

System requirements

The installation of Lis requires a C compiler. The Fortran interface requires a Fortran compiler, and the algebraic multigrid preconditioner requires a Fortran 90 compiler.[4] For parallel computing environments, an OpenMP or MPI library is used. Both the Harwell-Boeing and Matrix Market formats are supported to import and export user data.

Packages that use Lis

See also

References

  1. Akira Nishida (2010). "Experience in Developing an Open Source Scalable Software Infrastructure in Japan". Computational Science and Its Applications – ICCSA 2010. Lecture Notes in Computer Science 6017. Springer. pp. 87–98. doi:10.1007/978-3-642-12165-4_36. ISBN 3-642-12164-0.
  2. Hisashi Kotakemori, Hidehiko Hasegawa, Tamito Kajiyama, Akira Nukada, Reiji Suda, and Akira Nishida (2008). "Performance Evaluation of Parallel Sparse Matrix-Vector Products on SGI Altix 3700". OpenMP Shared Memory Parallel Programming. Lecture Notes in Computer Science 4315. Springer. pp. 153–163. doi:10.1007/978-3-540-68555-5_13. ISBN 3-540-68554-5.
  3. Hisashi Kotakemori, Hidehiko Hasegawa, and Akira Nishida (2005). "Performance Evaluation of a Parallel Iterative Method Library using OpenMP". Proceedings of the 8th International Conference on High Performance Computing in Asia Pacific Region (HPC Asia 2005). IEEE. pp. 432–436. doi:10.1109/HPCASIA.2005.74. ISBN 0-7695-2486-9.
  4. Akihiro Fujii, Akira Nishida, and Yoshio Oyanagi (2005). "Evaluation of Parallel Aggregate Creation Orders : Smoothed Aggregation Algebraic Multigrid Method". High Performance Computational Science and Engineering. Springer. pp. 99–122. doi:10.1007/0-387-24049-7_6. ISBN 1-4419-3684-X.

External links

This article is issued from Wikipedia - version of the Monday, March 28, 2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.