HP MLIB User's Guide Vol. 2 7th Ed.

Chapter 13 Sparse Linear Equations 877
What you need to know to use these subprograms
George, J.A. and J.W. Liu. Computer Solution of Large Sparse Positive Definite
Systems. Englewood Cliffs, NJ: Prentice-Hall, Inc. 1981.
George, A.; Liu, J. W. H. The Evolution of the Minimum Degree Ordering
Algorithm. SIAM Review, Vol. 31, pp1-19, 1989.
Heath, M.T., E. Ng, and B.W. Peyton. “Parallel Algorithms for Sparse Linear
Systems.” SIAM Review. September, 1991. Vol. 33, No. 3. pp. 420-460.
Karypis, G.; Kumar, V. A Fast and High Quality Multilevel Scheme for
Partitioning Irregular Graphs. SIAM J. on Scientific Computing, Vol. 20,
pp359-392, 1998.
What you need to know to use these subprograms
Data types
For solving sparse systems of linear equations with matrix structure input by
matrix, HP MLIB supports five data types:
• REAL*4
• REAL*8
• REAL*16
• COMPLEX*8
• COMPLEX*16
For solving sparse systems of linear equations with matrix structure input by
elements, columns, and finite elements, HP MLIB supports REAL*8 precision.
This chapter describes all subprograms using double precision data types.
Different input matrix formats can be intermixed to assign values to a matrix.
If the input format is defined to be by matrix, values can also be assigned using
input by elements, columns, and finite elements in all five data types.
Conversely, if the input format is defined to be by either elements, columns, or
finite elements, values can also be assigned using input by matrix, but only in
double precision
For matrix structure input by matrix, HP MLIB can be used to solve multiple
right-hand sides.