CUDAlign 3.0: Parallel biological sequence comparison in large GPU clusters
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EditorInstitute of Electrical and Electronics Engineers (IEEE)
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This paper proposes and evaluates a parallel strategy to execute the e+ xact Smith-Waterman (SW) biological sequence comparison algorithm for huge DNA sequences in multi-GPU platforms. In our strategy, the computation of a single huge SW matrix is spread over multiple GPUs, which communicate border elements to the neighbour, using a circular buffer mechanism. We also provide a method to predict the execution time and speedup of a comparison, given the number of the GPUs and the sizes of the sequences. The results obtained with a large multi-GPU environment show that our solution is scalable when varying the sizes of the sequences and/or the number of GPUs and that our prediction method is accurate. With our proposal, we were able to compare the largest human chromosome with its homologous chimpanzee chromosome (249 Millions of Base Pairs (MBP) x 228 MBP) using 64 GPUs, achieving 1.7 TCUPS (Tera Cells Updated per Second). As far as we know, this is the largest comparison ever done using the Smith-Waterman algorithm.
CitacióDe Sandes, E. [et al.]. CUDAlign 3.0: Parallel biological sequence comparison in large GPU clusters. A: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. "2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014): Chicago, Illinois: USA, 26-29 May 2014". Chicago, IL: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 160-169.
Versió de l'editorhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6846451
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