Preliminary results in accelerating profile HMM search on FPGAs

Comparison between biosequences and probabilistic models is an increasingly important part of modern DNA and protein sequence analysis. The large and growing number of such models in today's databases demands computational approaches to searching these databases faster, while maintaining high sensitivity to biologically meaningful similarities. This work describes an FPGA-based accelerator for comparing proteins to hidden Markov models of the type used to represent protein motifs in the popular HM-MER motif finder. Our engine combines a systolic array design with enhancements to pipeline the complex Viterbi calculation that forms the core of the comparison, and to support coarse-grained parallelism and streaming of multiple sequences within one FPGA. Performance estimates based on a functioning VHDL realisation of our design show a 190 times speedup over the same computation in optimised software on a modern general-purpose CPU.