A Complete CPU-FPGA Architecture for Protein Identification with Tandem Mass Spectrometry
| Autor: | Liang Zhao, Tao Chen, Yunping Zhu, Lingli Wang, Moucheng Yang, Xuegong Zhou |
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| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Profiling (computer programming) Speedup Matching (graph theory) Computer science business.industry 010401 analytical chemistry Process (computing) 01 natural sciences 0104 chemical sciences 03 medical and health sciences 030104 developmental biology Embedded system Scalability Hardware acceleration Database search engine Field-programmable gate array business |
| Zdroj: | FPT |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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