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The 15th Workshop on Languages and Compilers for Parallel Computing was held in July 2002 at the University of Maryland, College Park. It was jointly sponsored by the Department of Computer Science at the University of Ma- land and the University of Maryland Institute for Advanced Computer Studies (UMIACS).LCPC2002broughttogetherover60researchersfromacademiaand research institutions from many countries. The program of 26 papers was selected from 32 submissions. Each paper was reviewed by at least three Program Committee members and sometimes by additional reviewers. Prior to the workshop, revised versions of accepted papers were informally published on the workshop's website and in a paper proceedings that was distributed at the meeting. This year, the workshopwas organizedinto sessions of papers on related topics, and each session consisted of two to three 30-minute presentations.Based on feedback from the workshop, the papers were revised and submitted for inclusion in the formal proceedings published in this volume. Two papers were presented at the workshop but later withdrawn from the ?nal proceedings by their authors. We were very lucky to have Bill Carlson from the Department of Defense give the LCPC 2002 keynote speech on "UPC: A C Language for Shared M- ory Parallel Programming." Bill gave an excellent overview of the features and programming model of the UPC parallel programming language.
This book constitutes the thoroughly refereed post-proceedings of the 13th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2000, held in Yorktown Heights, NY, USA, in August 2000. The 22 revised full papers presented together with 5 posters were carefully selected during two rounds of reviewing and improvement. All current aspects of parallel processing are addressed with emphasis on issues in optimizing compilers, languages, and software environments in high-performance computing.
The field of bioinformatics and computational biology arose due to
the need to apply techniques from computer science, statistics,
informatics, and applied mathematics to solve biological problems.
Scientists have been trying to study biology at a molecular level
using techniques derived from biochemistry, biophysics, and
genetics. Progress has greatly accelerated with the discovery of
fast and inexpensive automated DNA sequencing techniques.
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