Molecular Docking on FPGA and GPU Platforms

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Abstract
Molecular docking is an important problem of bioinformatics aiming at the prediction of binding poses of molecules. Auto Dock is a popular, open-source docking software applying a computationally expensive but parallelizable algorithm. This paper introduces an FPGA-based and a GPU-based implementation of Auto Dock and shows how the original algorithm can be effectively accelerated on the two different platforms. According to test runs, both implementations achieve significant speedups over Auto Dock running on a single CPU core and on a quad-core system. Comparison of the two implementations proves that many-core graphics processing units can be a real alternative to FPGAs in the field of high performance computing.