A Reconfigurable Accelerator for Parallel Longest Common Protein Subsequence Algorithm

The problem of longest common subsequence is defined as finding the longest subsequence common to two input sequences. It can be employed in many fields such as speech and signal processing, data compression, syntactic pattern recognition, string processing (bioinformatics), and genetic engineering. This paper describes the design of a parallel longest common protein subsequence hardware, implemented in a FPGA device, using a dynamic programming (DP) algorithm. Such algorithms have computational complexity proportional to the length product of both involved sequences. Usually, lengths of both input sequences are very long, resulting in long processing time. The data dependency in DP imposes a serious constraint on the algorithm, not allowing its direct parallelization. To alleviate this serious problem, a reconfigurable accelerator for DP algorithm is presented. The main features include: a multistage PE (processing element) design with even stage delay which significantly reduces the FPGA resource usage and hence allows more parallelism to be exploited; and a pipelined control mechanism. Basing on these two techniques, the proposed accelerator can reach at 82-MHz frequency in an Altera EP1S30 device. This accelerator provides more than 660 speedup as compared to a standard desktop platform with a 2.8-GHz Xeon processor and 4-GB memory. Results show that reconfigurable computing can offer interesting solutions for bioinformatics problems.