Abstract

Provided are parallel computational methods and their implementation on memory-distributed architectures for a peptide identification tool, called HiCOPS, that enables more than 100-fold improvement in speed over existing HPC proteome database search tools. HiCOPS empowers the supercomputing database search for comprehensive identification of peptides and all their modified forms within a reasonable timeframe. Searching Gigabytes of experimen tal mass spectrometry data against Terabytes of databases demonstrates peptide identification in minutes compared to days or weeks, providing multiple orders of magnitude improvements in processing times. Also provided is a theo retical framework for a novel overhead-avoiding strategy, resulting in superior performance evaluation results for key metrics including execution time, CPU utilization, and I/O efficiency. a