OAK RIDGE NATIONAL LABORATORY U.S. DEPARTMENT OF ENERGY Cluster Computing Applications Cluster Computing Applications Project Project Parallelizing BLAST Parallelizing BLAST Research Alliance of Minorities (RAM), Computer Science and Mathematics Division William Burke York College, City University of New York John Mugler and Stephen Scott Oak Ridge National Laboratory
Cluster Computing Applications Project Parallelizing BLAST. William Burke York College, City University of New York John Mugler and Stephen Scott Oak Ridge National Laboratory. Research Alliance of Minorities (RAM), Computer Science and Mathematics Division. - PowerPoint PPT Presentation
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
OAK RIDGE NATIONAL LABORATORYU.S. DEPARTMENT OF ENERGY
OAK RIDGE NATIONAL LABORATORYU.S. DEPARTMENT OF ENERGY
Conclusion
BLAST algorithm has a diverse family
of programs.
Several implementations exist for parallelizing the BLAST algorithm.
Future work to include further
exploration of the various parallelized
BLAST algorithms on clusters.
OAK RIDGE NATIONAL LABORATORYU.S. DEPARTMENT OF ENERGY
Acknowledgements
I would like to extend my thanks to Stephen L. Scott,
John Mugler, Thomas Naughton, and Brian Luethke for
their invaluable mentoring, Michaelangelo Salcedo for
his guidance, Debbie McCoy and Cheryl Hamby for their
support in the RAM program.
OAK RIDGE NATIONAL LABORATORYU.S. DEPARTMENT OF ENERGY
Disclaimer
This research was performed under the Research Alliance for Minorities Program administered through the Computer Science and Mathematics Division, Oak Ridge National Laboratory. This Program is sponsored by the Mathematical, Information, and Computational Sciences Division; Office of Advanced Scientific Computing Research; U.S. Department of Energy. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. This research used resources of the Center for Computational Sciences at Oak Ridge National Laboratory, which is supported by the Office of Science, U.S. Department of Energy. This work has been authored by a contractor of the U.S. Government under contract DE-AC05-00OR22725. Accordingly, the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.