Paper Info
Title
A Complete CPU-FPGA Architecture for Protein Identification with Tandem Mass Spectrometry
Abstract
Tandem mass spectrometry-based database searching has currently been a significant technique for protein identification in proteomics. The ever-growing protein databases induce severe challenges for efficient database searching engines. Profiling analysis shows that X!Tandem, one of the most widely used open-source database search engines for protein identification, spends almost 78% of the total time on the scoring process. In this paper, field programmable gate arrays (FPGAs) are used as hardware accelerators due to their ability to parallelize arithmetic operations and execute loops in parallel. A scalable heterogeneous CPU-FPGA architecture is proposed to speed up the whole process of X!Tandem, in which parent ion matching and scoring are implemented on FPGAs. The hardware implementation of the scoring process running on one Xilinx Kintex UltraScale FPGA board (XCKU115) at 150 MHz can achieve 21-fold speedup over original X!Tandem software implementation running on a CPU, while the complete CPU-FPGA architecture, which consists of two FPGA boards, achieves more than 10-fold speedup over CPU-only implementation as far as the whole process of protein identification is concerned.
Year
DOI
Venue
2019
10.1109/ICFPT47387.2019.00051
2019 International Conference on Field-Programmable Technology (ICFPT)
Keywords
Field
DocType
FPGA,Protein Identification,Hardware Acceleration
Protein identification,Computer science,Profiling (computer programming),Tandem mass spectrometry,Parallel computing,Database search engine,Field-programmable gate array,Hardware acceleration,Scalability,Speedup
Conference
ISBN
Citations 
PageRank 
978-1-7281-2944-0
0
0.34
References 
Authors
2
6
Name
Order
Citations
PageRank
Moucheng Yang101.69
Tao Chen262.19
Xuegong Zhou3416.28
Liang Zhao400.34
Yunping Zhu500.34
Lingli Wang68625.42