# LDRD final report on massively-parallel linear programming : the parPCx system.

@inproceedings{Parekh2005LDRDFR, title={LDRD final report on massively-parallel linear programming : the parPCx system.}, author={Ojas Parekh and Cynthia A. Phillips and Erik G. Boman}, year={2005} }

- Published 2005
DOI:10.2172/921147

This report summarizes the research and development performed from October 2002 to September 2004 at Sandia National Laboratories under the Laboratory-Directed Research and Development (LDRD) project ''Massively-Parallel Linear Programming''. We developed a linear programming (LP) solver designed to use a large number of processors. LP is the optimization of a linear objective function subject to linear constraints. Companies and universities have expended huge efforts over decades to produce… CONTINUE READING

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## Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication

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## Simultaneous Input and Output Matrix Partitioning for Outer-Product-Parallel Sparse Matrix-Matrix Multiplication

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## Graph/hypergraph partitioning models for simultaneous load balancing on computation and data

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## Exploiting Locality in Sparse Matrix-Matrix Multiplication on Many-Core Architectures

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## Expected losses

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## Maximum-weight-basis preconditioners

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## Nearly linear time algorithms for graph par-titioning

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## Polyhedral combinatorics

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