A high-performance reconfigurable computing solution for Peptide mass fingerprinting.
High-throughput, MS-based proteomics studies are generating very large volumes of biologically relevant data. Given the central role of proteomics in emerging fields such as system/synthetic biology and biomarker discovery, the amount of proteomic data is expected to grow at unprecedented rates over the next decades. At the moment, there is pressing need for high-performance computational solutions to accelerate the analysis and interpretation of this data.Performance gains achieved by grid computing in this area are not spectacular, especially given the significant power consumption, maintenance costs and floor space required by large server farms.This paper introduces an alternative, cost-effective high-performance bioinformatics solution for peptide mass fingerprinting based on Field Programmable Gate Array (FPGA) devices. At the heart of this approach stands the concept of mapping algorithms on custom digital hardware that can be programmed to run on FPGA. Specifically in this case, the entire computational flow associated with peptide mass fingerprinting, namely raw mass spectra processing and database searching, has been mapped on custom hardware processors that are programmed to run on a multi-FPGA system coupled with a conventional PC server. The system achieves an almost 2,000-fold speed-up when compared with a conventional implementation of the algorithms in software running on a 3.06 GHz Xeon PC server.
Coca
Daniel
D
Department of Automatic Control & Systems Engineering, University of Sheffield, Sheffield, UK. d.coca@sheffield.ac.uk
Bogdan
Istvan
I
Beynon
Robert J
RJ
D000465:Algorithms; D003201:Computers; D003205:Computing Methodologies; D030562:Databases, Protein; D004867:Equipment Design; D013058:Mass Spectrometry / Q000379:methods*; D010449:Peptide Mapping / Q000191:economics / Q000379:methods*; D040901:Proteomics / Q000191:economics / Q000379:methods*