2/14/2023 0 Comments Driver nvidia model p561 cOur proposed strategy uses GPU specific optimizations that do not rely on the nature of sequence. In this paper, we present ADEPT, a new sequence alignment strategy for GPU architectures that is domain independent, supporting alignment of sequences from both genomes and proteins. Existing GPU based strategies have either been optimized for a specific type of characters (Nucleotides or Amino Acids) or for only a handful of application use-cases. However, with the move of HPC facilities towards accelerator based architectures, a need for an efficient GPU accelerated strategy has emerged. Multiple SIMD strategies for the Smith-Waterman algorithm are available for CPUs. With the advent of modern sequencing technologies and increasing size of both genome and protein databases, a need for faster Smith-Waterman implementations has emerged. This task is performed with the Smith-Waterman algorithm, which is a dynamic programming based method. At the core of most of these tools, a significant portion of execution time is spent in determining optimal local alignment between two sequences. Bioinformatic workflows frequently make use of automated genome assembly and protein clustering tools.
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