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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.

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Correspondence to John Paul Walters.

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John Paul Walters: This research was supported in part by NSF IGERT grant 9987598 and the Institute for Scientific Computing at Wayne State University.

Vipin Chaudhary: This research was supported in part by NSF IGERT grant 9987598, the Institute for Scientific Computing at Wayne State University, MEDC/Michigan Life Science Corridor, and NYSTAR.

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Walters, J.P., Meng, X., Chaudhary, V. et al. MPI-HMMER-Boost: Distributed FPGA Acceleration. J VLSI Sign Process Syst Sign Im 48, 223–238 (2007). https://doi.org/10.1007/s11265-007-0062-9

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  • DOI: https://doi.org/10.1007/s11265-007-0062-9

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