May 23, 2009 to May 29, 2009
John Paul Walters , Department of Computer Science and Engineering, University at Buffalo, SUNY, NY, USA
Vidyananth Balu , Department of Computer Science and Engineering, University at Buffalo, SUNY, NY, USA
Suryaprakash Kompalli , Hewlett-Packard Laboratories, Bangalore, India
Vipin Chaudhary , Department of Computer Science and Engineering, University at Buffalo, SUNY, NY, USA
In this paper we present the results of parallelizing two life sciences applications, Markov random fields-based (MRF) liver segmentation and HMMER's Viterbi algorithm, using GPUs. We relate our experiences in porting both applications to the GPU as well as the techniques and optimizations that are most beneficial. The unique characteristics of both algorithms are demonstrated by implementations on an NVIDIA 8800 GTX Ultra using the CUDA programming environment. We test multiple enhancements in our GPU kernels in order to demonstrate the effectiveness of each strategy. Our optimized MRF kernel achieves over 130× speedup, and our hmmsearch implementation achieves up to 38× speedup. We show that the differences in speedup between MRF and hmmsearch is due primarily to the frequency at which the hmmsearch must read from the GPU's DRAM.
John Paul Walters, Vidyananth Balu, Suryaprakash Kompalli, Vipin Chaudhary, "Evaluating the use of GPUs in liver image segmentation and HMMER database searches", IPDPS, 2009, Parallel and Distributed Processing Symposium, International, Parallel and Distributed Processing Symposium, International 2009, pp. 1-12, doi:10.1109/IPDPS.2009.5161073