MPI-HMMER-Boost: Distributed FPGA Acceleration

Authors:
John Paul Walters;Xiandong Meng;Vipin Chaudhary;Tim Oliver;Leow Yuan Yeow;Bertil Schmidt;Darran Nathan;Joseph Landman
Affiliations:
Institute for Scientific Computing, Wayne State University, Detroit, USA 48202;Electrical and Computer Engineering Department, Wayne State University, Detroit, USA 48202;Department of Computer Science and Engineering University at Buffalo, The State University of New York, Buffalo, USA 14260;Progeniq Pte Ltd., Singapore, Singapore 118407;Progeniq Pte Ltd., Singapore, Singapore 118407;UNSW Asia, Queenstown, Singapore 248922;Progeniq Pte Ltd., Singapore, Singapore 118407;Scalable Informatics LLC, Canton, USA 48188
Venue:
Journal of VLSI Signal Processing Systems
Year:
2007

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Abstract

HMMER, based on the profile Hidden Markov Model (HMM) is one of the most widely used sequence database searching tools, allowing researchers to compare HMMs to sequence databases or sequences to HMM databases. Such searches often take many hours and consume a great number of CPU cycles on modern computers. We present a cluster-enabled hardware/software-accelerated implementation of the HMMER search tool hmmsearch. Our results show that combining the parallel efficiency of a cluster with one or more high-speed hardware accelerators (FPGAs) can significantly improve performance for even the most time consuming searches, often reducing search times from several hours to minutes.