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2005
Springer

High-Performance Algorithm Engineering for Large-Scale Graph Problems and Computational Biology

8 years 9 months ago
High-Performance Algorithm Engineering for Large-Scale Graph Problems and Computational Biology
Abstract. Many large-scale optimization problems rely on graph theoretic solutions; yet high-performance computing has traditionally focused on regular applications with high degrees of locality. We describe our novel methodology for designing and implementing irregular parallel algorithms that attain significant performance on high-end computer systems. Our results for several fundamental graph theory problems are the first ever to achieve parallel speedups. Specifically, we have demonstrated for the first time that significant parallel speedups are attainable for arbitrary instances of a variety of graph problems and are developing a library of fundamental routines for discrete optimization (especially in computational biology) on shared-memory systems. Phylogenies derived from gene order data may prove crucial in answering some fundamental questions in biomolecular evolution. Highperformance algorithm engineering offers a battery of tools that can reduce, sometimes spectacular...
David A. Bader
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where WEA
Authors David A. Bader
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