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Hadoop-MCC: Efficient Multiple Compound Comparison Algorithm Using Hadoop

Author(s):

Guan-Jie Hua, Che-Lun Hung* and Chuan Yi Tang  

Abstract:


In this paper, we propose a novel heterogeneous high performance computing method, named as Hadoop-MCC, integrating Hadoop and GPU, to compare huge amount of chemical structures efficiently. The proposed method gains the high availability and fault tolerance from Hadoop, as Hadoop is used to scatter input data to GPU devices and gather the results from GPU devices. A comparison of LINGO is performed on each GPU device in parallel. According to the experimental results, the proposed method on multiple GPU devices can achieve better computational performance than the CUDA-MCC on a single GPU device.

Keywords:

LINGO, Hadoop, High Performance Computing, GPU, Big Data.

Affiliation:

Department of Computer Science, National Tsing Hua University, Hsinchu, Department of Computer Science and Communication Engineering, Providence University, Taichung, Department of Computer Science, National Tsing Hua University, Hsinchu



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