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The UCSC Kestrel Parallel Processor.

Authors :
Di Blas, Andrea
Dahle, David M.
Diekhans, Mark
Grate, Leslie
Hirschberg, Jeffrey
Karplus, Kevin
Keller, Hansjörg
Kendrick, Mark
Mesa-Martinez, Francisco J.
Pease, David
Rice, Eric
Schultz, Angela
Speck, Don
Hughey, Richard
Source :
IEEE Transactions on Parallel & Distributed Systems. Jan2005, Vol. 16 Issue 1, p80-92. 13p.
Publication Year :
2005

Abstract

The architectural landscape of high-performance computing stretches from superscalar uniprocessor to explicitly parallel systems to dedicated hardware implementations of algorithms. Single-purpose hardware can achieve the highest performance and uniprocessors can be the most programmable. Between these extremes, programmable and reconfigurable architectures provide a wide range of choice in flexibility, programmability, computational density, and performance. The UCSC Kestrel parallel processor strives to attain single-purpose performance while maintaining user programmability. Kestrel is a single-instruction stream, multiple- data stream (SIMD) parallel processor with a 512-element linear array of 8-bit processing elements. The system design focuses on efficient high-throughput DNA and protein sequence analysis, but its programmability enables high performance on computational chemistry, image processing, machine learning, and other applications. The Kestrel system has had unexpected longevity in its utility due to a careful design and analysis process. Experience with the system leads to the conclusion that programmable SIMD architectures can excel in both programmability and performance. This paper presents the architecture, implementation, applications, and observations of the Kestrel project at the University of California at Santa Cruz. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10459219
Volume :
16
Issue :
1
Database :
Academic Search Index
Journal :
IEEE Transactions on Parallel & Distributed Systems
Publication Type :
Academic Journal
Accession number :
15512996