![]() ![]() ![]() Schatz, Michael C Trapnell, Cole Delcher, Arthur L Varshney, Amitabhīackground The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. High-throughput sequence alignment using Graphics Processing Units The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU. Conclusions pps Align is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. We observed a 36-fold speedup over TM- align, a 65-fold speedup over Fr-TM- align, and a 40-fold speedup over MAMMOTH. We evaluated pps Align on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. As a general-purpose GPU platform, pps Align could take many concurrent methods, such as TM- align and Fr-TM- align, into the parallelized algorithm design. Findings We present pps Align, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs). Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. However, these solutions are costly and of limited accessibility. ![]() To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. ![]() Accelerating large-scale protein structure alignments with graphics processing unitsīackground Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. ![]()
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