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    Qian Lei, Zhao Jinming, Peng Dajia, Li Xiang, Wu Dong, Xie Xianghui. Energy-Efficient Fingerprint Matching Based on Reconfigurable Micro Server[J]. Journal of Computer Research and Development, 2016, 53(7): 1425-1437. DOI: 10.7544/issn1000-1239.2016.20160076
    Citation: Qian Lei, Zhao Jinming, Peng Dajia, Li Xiang, Wu Dong, Xie Xianghui. Energy-Efficient Fingerprint Matching Based on Reconfigurable Micro Server[J]. Journal of Computer Research and Development, 2016, 53(7): 1425-1437. DOI: 10.7544/issn1000-1239.2016.20160076

    Energy-Efficient Fingerprint Matching Based on Reconfigurable Micro Server

    • Large-scale fingerprint based application needs high-performance fingerprint matching backend system as a support. Based on reconfigurable micro server(RMS) technology, we propose a software-hardware cooperated fingerprint matching approach. Relying on the advantages of reconfigurable hybrid core computing architecture, our approach can accelerate the computing intensive part of fingerprint matching algorithm by using highly customized hardware accelerator and process the parts which contain complex control flows and a large number of discrete memory accesses on general processing cores. Then, we complete the implementation of algorithm prototype and the performance test on RMS computing node. The test result shows that, single RMS node can achieve about 10,500 fingerprint matches per second with only 5 watts power consumption. Compared with related works, the fingerprint matching performance of a single RMS computing node is 15.5 times that of a single X86 cluster node. Its energy efficiency is 583 times of single X86 cluster node and 5.4 times of Tesla C2075 based GPU server. Based on RMS technology, our method is more flexible and extensible than FPGA platform. It is expected to become an effective technique solution for building large-scale fingerprint matching system in the future.
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