This is suite of functions for manipulating sparse matrices. Please look at the SuiteSparse homepage for details about usage and available functions.

Setting the module environment

When you log in, you should load your preferred compiler module, the Intel compiler is loaded by default. As the SuiteSparse functions depend on BLAS and LAPACK, you will also need to load an implementation of these libraries, several are installed on the system. For example, if you would like to use the PGI compiler and MKL, Intel’s implementation of the numerical libraries, use:

module switch intel pgi
module add mkl
module add suitesparse

This will add the packages appropriate for your chosen environment.



This module provides the following packages:

Package Version Description
AMD 2.2.2 Symmetric approximate minimum degree
BTF 1.1.2 Permutation to block triangular form
CAMD 2.2.2 Symmetric approximate minimum degree
CCOLAMD 2.7.3 Constrained column minimum degree
COLAMD 2.7.3 Column approximate minimum degree
CHOLMOD 1.7.3 Sparse supernodal Cholesky factorization and update/downdate
CSparse 2.2.5 A concise sparse matrix package
CXSparse 2.2.5 An extended version of CSparse
KLU 1.1.1 Sparse LU factorization, for circuit simulation
LDL 2.0.3 A simple LDL factorization
UMFPACK 5.5.1 Sparse multifrontal LU factorisation
MESHND 1.1.1 2D and 3D mesh generation and nested dissection
SuiteSParseQR 1.2.1 Multifrontal sparse QR