Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers

Reconfigurable computing technology has progressed to a stage where it is now pos-sible to achieve orders of magnitude performance and power efficiency gains over conventional computer architectures for a subset of high performance computing ap-plications. In this thesis, we investigate the potential of reconfigurable computers to accelerate genomic sequence alignment specifically for genome sequencing applica-tions. We present a highly optimized implementation of a parallel sequence alignment algorithm for the Berkeley Emulation Engine (BEE2) reconfigurable computer, al-lowing a single BEE2 to align simultaneously hundreds of sequences. For each recon-figurable processor (FPGA), we demonstrate a 61X speedup versus a state-of-the-art implementation on a modern conventional CPU core, and a 56X improvement in performance-per-Watt. We also show that our implementation is highly scalable and we provide performance results from a cluster implementation using 32 FPGAs. We conclude that reconfigurable computers provide an excellent platform on whic