GPU-accelerated Peptide Search

Award Information
Agency: Department of Health and Human Services
Branch: N/A
Contract: 1R43HG006414-01
Agency Tracking Number: R43HG006414
Amount: $203,600.00
Phase: Phase I
Program: SBIR
Awards Year: 2011
Solicitation Year: 2011
Solicitation Topic Code: NHGRI
Solicitation Number: PA10-050
Small Business Information
INSILICOS
111 Queen Anne Ave N., #500, SEATTLE, WA, -
DUNS: 126643241
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 BRIAN PRATT
 (206) 979-4832
 brian.pratt@insilicos.com
Business Contact
 ERIK NILSSON
Phone: (206) 321-5743
Email: brian.pratt@insilicos.com
Research Institution
 Stub
Abstract
DESCRIPTION (provided by applicant): The use of Graphics Processing Unit (GPU) devices is proposed to increase the speed of peptide search by as much as an order of magnitude. Peptide search engines perform the most computation-intensive task in shotgun proteomics. This proposal is to speed up peptide search using the increasingly popular approach of general-purpose computation on highly-parallel GPU devices. Computation using GPUs to gain desktop supercomputer performance at low cost is an active and fruitful area of research. This project will obtain these benefits for peptide search. As a result, researchers will be able to take experiments that today must be analyzed on a computer cluster, and instead analyze them on their desktop computer. PUBLIC HEALTH RELEVANCE: A enhancement to the popular peptide search engine X Tandem is proposed, to allow it to run in parallel on graphics processing unit (GPU) cards with dramatically faster performance. This will allow much faster and less-expensive operation, allowing proteomics researchers to analyze large proteomics experiments or search for post- translational modifications (PTMs) using their existing desktop computer. Proteomics has led to many important advances in biological understanding. Yet, manyvaluable data sets are not searched for PTMs, simply because the computer power necessary to conduct the searches is not available. With this project, we plan to substantially reduce the computational cost of proteomics experiments, via a peptide search engine making use of inexpensive, highly parallel GPU hardware. Thus, this project, if successful, will allow proteomics to be more successfully exploited for public health. The research team is well-qualified to undertake this research, having extensive, direct experience in all the scientific disciplines and specific software elements necessary. The research team includes experts in proteomics, mass spectrometry, peptide search, and GPU computing.

* information listed above is at the time of submission.

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