Low power DNA protein sequence alignment using FSM state transition controller

Abstract

In this paper we proposed an efficient computation technique for DNA patterns on reconfigurable hardware (FPGAs) platform. The paper also presents the results of a comparative study between existing dynamic and heuristic programming methods of the widely-used Smith-Waterman pair-wise sequence alignment algorithm with FSM-based core implementation. Traditional software implication-based sequence alignment methods can not meet the actual data rate requirements. Hardware-based approach will give high scalability and one can process parallel tasks with a large number of new databases. This paper explains finite state machine (FSM)-based core processing element to classify the protein sequence. In addition, we analyse the performance of bit-based sequence alignment algorithms and present the inner stage pipelined field programmable gate array (FPGA) architecture for sequence alignment implementations. Here, synchronised controllers are used to carry out parallel sequence alignment. The complete architecture is designed to carry out parallel processing in hardware, with FSM-based bit wised pattern comparison with scalability as well as with a minimum number of computations. Finally, the proposed design proved to be high performance and its efficiency in terms of resource utilisation is proved on FPGA implementation.