DocumentCode :
2787448
Title :
RAxML-Cell: Parallel Phylogenetic Tree Inference on the Cell Broadband Engine
Author :
Blagojevic, Filip ; Stamatakis, Alexandros ; Antonopoulos, Christos D. ; Nikolopoulos, Dimitrios S.
Author_Institution :
Dept. of Comput. Sci., Virginia Tech., Blacksburg, VA
fYear :
2007
fDate :
26-30 March 2007
Firstpage :
1
Lastpage :
10
Abstract :
Computational phylogeny is a challenging application even for the most powerful supercomputers. It is also an ideal candidate for benchmarking emerging multiprocessor architectures, because it exhibits fine- and coarse-grain parallelism at multiple levels. In this paper, we present the porting, optimization, and evaluation of RAxML on the cell broadband engine. RAxML is a provably efficient, hill climbing algorithm for computing phylogenetic trees, based on the maximum likelihood (ML) method. The cell broadband engine, a heterogeneous multi-core processor with SIMD accelerators which was initially marketed for set-top boxes, is currently being deployed on supercomputers and high-end server architectures. We present both conventional and unconventional, cell-specific optimizations for RAxML´s search algorithm on a real cell multiprocessor. While exploring these optimizations, we present solutions to problems related to floating point code execution, complex control flow, communication, scheduling, and multilevel parallelization on the cell.
Keywords :
DNA; biology computing; evolution (biological); genetics; maximum likelihood estimation; multiprocessing systems; parallel machines; tree searching; DNA; RAxML-cell; SIMD accelerator; benchmark; cell broadband engine; hill climbing algorithm; maximum likelihood method; multiprocessor architecture; parallel phylogenetic tree inference; search algorithm; supercomputer; Computer architecture; Computer science; Concurrent computing; Engines; Microprocessors; Military computing; Multicore processing; Parallel processing; Phylogeny; Supercomputers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0910-1
Electronic_ISBN :
1-4244-0910-1
Type :
conf
DOI :
10.1109/IPDPS.2007.370267
Filename :
4227995
Link To Document :
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