This paper presents a GPU-based high performance computing method for the protein-DNA docking problem. The protein-DNA docking algorithm in consideration integrates Monte-Carlo simulation and simulated annealing method. We investigate key factors that affect performance on a GPU cluster. These include the arrangement of the computation kernel and the balance between memory coalescing and path divergence. We also compared different Monte-Carlo schemes with respects to computation cost and prediction accuracy. With optimizations of these design options, our algorithm achieved 10.4 TFLOPS of sustained performance using 128 Tesla M2070 GPU cards, which represents 3.6x speed up over a traditional cluster with 1000...