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Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems

Jaideep Singh, Ipseeta Aruni
Indian Institute of Technology Roorkee Roorkee, India
5th International Conference on Bioinformatics and Biomedical Engineering, (iCBBE) 2011

@inproceedings{singh2011accelerating,

   title={Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems},

   author={Singh, J. and Aruni, I.},

   booktitle={Bioinformatics and Biomedical Engineering,(iCBBE) 2011 5th International Conference on},

   pages={1–4},

   organization={IEEE},

   year={2011}

}

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This paper describes the approach and the speedup obtained in performing Smith-Waterman database searches on heterogeneous platforms comprising of multi core CPU and multi GPU systems. Most of the advanced and optimized Smith-Waterman algorithm versions have demonstrated remarkable speedup over NCBI BLAST versions, viz., SWPS3 based on x86 SSE2 instructions and CUDASW++ v2.0 CUDA implementation on GPU. This work proposes a hybrid Smith-Waterman algorithm that integrates the state-of-the art CPU and GPU solutions for accelerating Smith-Waterman algorithm in which GPU acts as a co-processor and shares the workload with the CPU enabling us to realize remarkable performance of over 70 GCUPS resulting from simultaneous CPU-GPU execution. In this work, both CPU and GPU are graded equally in performance for Smith-Waterman rather than previous approaches of porting the computationally intensive portions onto the GPUs or a naive multi-core CPU approach.
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