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» Run-Time Techniques for Parallelizing Sparse Matrix Problems
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SC
2003
ACM
13 years 10 months ago
Parallel Multilevel Sparse Approximate Inverse Preconditioners in Large Sparse Matrix Computations
We investigate the use of the multistep successive preconditioning strategies (MSP) to construct a class of parallel multilevel sparse approximate inverse (SAI) preconditioners. W...
Kai Wang, Jun Zhang, Chi Shen
ICML
2006
IEEE
14 years 5 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
EUROPAR
1998
Springer
13 years 9 months ago
Parallel Sparse Matrix Computations Using the PINEAPL Library: A Performance Study
Abstract. The Numerical Algorithms Group Ltd is currently participating in the European HPCN Fourth Framework project on Parallel Industrial NumErical Applications and Portable Lib...
Arnold R. Krommer
ICCSA
2003
Springer
13 years 10 months ago
Coarse-Grained Parallel Matrix-Free Solution of a Three-Dimensional Elliptic Prototype Problem
The finite difference discretization of the Poisson equation in three dimensions results in a large, sparse, and highly structured system of linear equations. This prototype prob...
Kevin P. Allen, Matthias K. Gobbert
PPSC
1997
13 years 6 months ago
Improving Memory-System Performance of Sparse Matrix-Vector Multiplication
Sparse matrix-vector multiplication is an important kernel that often runs inefficiently on superscalar RISC processors. This paper describes techniques that increase instruction-...
Sivan Toledo