Reconfigurable Systems for the Zuker and Predator Algorithms for Secondary Structure Prediction of Genetic Data

Secondary structure prediction is a compute-intensive task that is used in many bioinformatics applications. In this paper we have selected two of the most well-known secondary structure prediction algorithms, the Predator and the Zuker algorithm, and we present two FPGA-based systems that implement them. Also, this paper presents different schemes of data reuse and data organization of structure prediction systems to avoid the data I/O bottleneck. The speedup of the execution time is at least 37x for the Predator method and 3x for the Zuker method compared to the corresponding software implementations. Finally, this paper shows that the exploitation of FPGA capabilities offers high performance systems that can be used by the bioinformatics community.