Direct methods for sparse matrices
Direct methods for sparse matrices
A comparative study of algorithms for matrix balancing
Operations Research
Scaling Matrices to Prescribed Row and Column Maxima
SIAM Journal on Matrix Analysis and Applications
Hypergraph-Partitioning-Based Decomposition for Parallel Sparse-Matrix Vector Multiplication
IEEE Transactions on Parallel and Distributed Systems
Equilibration of Symmetric Matrices in the Max-Norm
Journal of the ACM (JACM)
Partitioning Rectangular and Structurally Unsymmetric Sparse Matrices for Parallel Processing
SIAM Journal on Scientific Computing
On Algorithms For Permuting Large Entries to the Diagonal of a Sparse Matrix
SIAM Journal on Matrix Analysis and Applications
A Fine-Grain Hypergraph Model for 2D Decomposition of Sparse Matrices
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
SIAM Journal on Scientific Computing
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We recently proposed an iterative procedure which asymptotically scales the rows and columns of a given matrix to one in a given norm. In this work, we briefly mention some of the properties of that algorithm and discuss its efficient parallelization. We report on a parallel performance study of our implementation on a few computing environments.