Search Word(s) in Title, Keywords, Authors, and Abstract: Graphical Processing Unit

Accelerating Group Fusion for Ligand-Based Virtual Screening on Multi-core and Many-core Platforms
Mohd-Norhadri Mohd-Hilmi, Marwah Haitham Al-Laila and Nurul Hashimah Ahamed Hassain Malim
Page: 724~740, Vol. 12, No.4, 2016
10.3745/JIPS.01.0012

Keywords: Chemoinformatics, Graphical Processing Unit, Group Fusion, Open Multiprocessing, Virtual Screening
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The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized