An experimental study of optimizing bioinformatics applications
Guangming Tan
Lin Xu
Shengzhong Feng
Ninghui Sun
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing;
Abstract
As bioinformatics is an emerging application of high performance computing, this paper first evaluates the memory performance of several representative bioinformatics applications so that some appropriate optimization methods can be applied. Based on the computational behavior of these bioinformatics applications, we propose two optimized algorithms on high performance computer architectures. 1) For the data (I/O) intensive program, MegaBlast, we overlap computation with I/O to produce an improved high-throughput algorithm with reduced time and memory requirements. 2) For a CPU-intensive RNA secondary structure prediction algorithm, we propose a fine-grain parallel O(N3) algorithm based on reconfigurable arrays (FPGAs). In order to optimize the FPGA architecture, we evaluate the performance in different architectures using cycle-by-cycle simulator
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