NDLI: Evaluating Optimization Strategies for HMMer Acceleration on GPU

Content Provider	IEEE Xplore Digital Library
Author	Ferraz, S. Moreano, N.
Copyright Year	2013
Description	Author affiliation: Sch. of Comput., Fed. Univ. of Mato Grosso do Sul, Campo Grande, Brazil (Ferraz, S.; Moreano, N.)
Abstract	Comparing a biological sequence to a family of sequences is an important task in Bioinformatics, commonly performed using tools such as HMMer. The Viterbi algorithm is applied as HMMer main step to compute the similarity between the sequence and the family. Due to the exponential growth of biological sequence databases, implementations of the Viterbi algorithm on several high performance platforms have been proposed. Nevertheless, few implementations of the Viterbi algorithm use GPUs as main platform. In this paper, we present the development and optimization of an accelerator for the Viterbi algorithm applied to biological sequence analysis on GPUs. Some of the optimizations analyzed are applied to the sequence comparison problem for the first time in the literature and others are evaluated in more depth than in related works. Our main contributions are: (a) an accelerator that achieves speedups up to 102.90 and 60.46, with respect to HMMer2 and HMMer3 execution on a general purpose computer, respectively, (b) the use of the multi-platform OpenCL programming model for the accelerator, (c) a detailed evaluation of several optimizations such as memory, control flow, execution space, instruction scheduling, and loop optimizations, and (d) a methodology of optimizations and evaluation that can also be applied to other sequence comparison algorithms, such as the HMMer3 MSV.
Sponsorship	IEEE Tech. Comm. Distrib. Process.
Starting Page	59
Ending Page	68
File Size	1057789
Page Count	10
File Format	PDF
ISBN	9781479920815
ISSN	15219097
DOI	10.1109/ICPADS.2013.21
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-15
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Graphics processing units Viterbi algorithm Memory management Optimization Databases Parallel processing OpenCL Sequence-profile alignment GPU Accelerator
Content Type	Text
Resource Type	Article
Subject	Hardware and Architecture

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