Speeding up Scoring Module of Mass Spectrometry Based Protein Identification by GPUs
نویسنده
چکیده
Database searching is a main method for protein identification in shotgun proteomics, and till now most research effort is dedicated to improve its effectiveness. However, the efficiency of database searching is facing a serious challenge, due to the ever fast increasing of protein and peptide databases resulting from genome translations, enzymatic digestions, and post-translational modifications. On the other hand, as a general-purpose and high performance parallel hardware, Graphics Processing Units (GPUs) develop continuously and provide another promising platform for parallelizing database searching based protein identification to increase its efficiency. In this paper, we propose to systematically research on speeding up database search engines by GPUs for protein identification. Considering the scoring module is the most time-consuming part, we mainly utilize GPUs to speed it up. We choose two popular scoring method: firstly, SDP based method, which is chosen by X!Tandem, reaches a speedup of thirty to one hundred; secondly, KSDP, which is adopted by pFind, achieves a speedup of five to ten.
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