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Parallel Optimal Pairwise Biological Sequence Comparison: Algorithms, Platforms, and Classification
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DOI：10.1145/2893488.png)
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Abstract
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Many bioinformatics applications, such as the optimal pairwise biological sequence comparison, demand a great quantity of computing resource, thus are excellent candidates to run in high-performance computing (HPC) platforms. In the last two decades, a large number of HPC-based solutions were proposed for this problem that run in different platforms, targeting different types of comparisons with slightly different algorithms and making the comparative analysis of these approaches very difficult. This article proposes a classification of parallel optimal pairwise sequence comparison solutions, in order to highlight their main characteristics in a unifiedway. We then discuss several HPC-based solutions, including clusters ofmulticores and accelerators such as Cell Broadband Engines (CellBEs), Field-Programmable Gate Arrays (FPGAs), Graphics Processing Units (GPUs) and Intel Xeon Phi, as well as hybrid solutions, which combine two or more platforms, providing the actual landscape of the main proposals in this area. Finally, we present open questions and perspectives in this research field.
Keywords:
Algorithms
Performance
Parallel algorithms
biological sequence comparison
FPGA
GPU
multicores
CellBE
Intel Phi
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