Users' guide for the Harwell-Boeing sparse matrix collection (Release 1)

By Iain S. Duff, R. Grimes, J. G. Lewis. 1992

Subfields: Numerical Methods & Scientific Computing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Numerical Methods & Scientific Computing

1. Xiaoye Sherry Li
2. James Weldon Demmel
3. Dominique Orban
4. N. Gould
5. John R. Gilbert
6. Philippe L. Toint
7. J. Demmel
8. Natarajan Sukumar

Citations in the corpus

• SuperLU_DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems (2003, background): “Most of them, except for wu, can be obtained from the Harwell-Boeing Collection [Duff et al. 1992] and the collection of Davis [Davis n.”
• SuperLU Users'' Guide (1997, methodology): “The NC format is the same as the Harwell-Boeing sparse matrix format [6], that is, the compressed column storage.”
• Automatic Differentiation of Algorithms: From Simulation to Optimization (2002, methodology): “Our test problems are drawn from the Harwell-Boeing [167] test matrix collection.”
• CUTEr and SifDec: A constrained and unconstrained testing environment, revisited (2003, methodology): “To convert matrices (for example, Hessians, Jacobians, and KKT augmented system matrices) derived from SIF problem data into Harwell-Boeing [Duff et al. 1999, 1992] or Rutherford-Boeing [Duff et al. 1997] sparse matrix formats.”