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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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