Parallel and Distributed Processing Symposium, International (2008)
Miami, FL, USA
Apr. 14, 2008 to Apr. 18, 2008
Abhinav Sarje , Department of Electrical and Computer Engineering, Iowa State University, USA
Srinivas Aluru , Department of Electrical and Computer Engineering, Iowa State University, USA
Sequence alignment and its many variants are a fundamental tool in computational biology. There is considerable recent interest in using the Cell Broadband Engine, a heterogenous multi-core chip that provides high performance, for biological applications. However, work so far has been limited to computing optimal alignment scores using quadratic space under the basic global/local alignment algorithm. In this paper, we present a comprehensive study of developing sequence alignment algorithms on the Cell exploiting its thread and data level parallelism features. First, we develop a Cell implementation that computes optimal alignments and adopts Hirschberg’s linear space technique. The former is essential as merely computing optimal alignment scores is not useful while the latter is needed to permit alignments of longer sequences. We then present Cell implementations of two advanced alignment techniques — spliced alignments and syntenic alignments. In a spliced alignment, consecutive non-overlapping portions of a sequence align with ordered non-overlapping, but non-consecutive portions of another sequence. Spliced alignments are useful in aligning mRNA sequences with corresponding genomic sequences to uncover gene structure. Syntenic alignments are used to discover conserved exons and other sequences between long genomic sequences from different organisms. We present experimental results for these three types of alignments on the Cell BE and report speedups of about 4 on six SPUs on the Playstation 3, when compared to the respective best serial algorithms on the Cell BE and the Pentium 4 processor.
S. Aluru and A. Sarje, "Parallel biological sequence alignments on the Cell Broadband Engine," 2008 IEEE International Parallel & Distributed Processing Symposium(IPDPS), Miami, FL, 2008, pp. 1-11.