GPU acceleration of a production molecular docking code

ABSTRACT

Modeling the interactions of biological molecules, or docking, is critical to both understanding basic life processes and to designing new drugs. Here we describe the GPU-based acceleration of a recently developed, complex, production docking code. We show how the various functions can be mapped to the GPU and present numerous optimizations. We find which parts of the problem domain are best suited to the different correlation methods. The GPU-accelerated system achieves a speedup of at least 17.7x with respect to a single core and 6.1x with respect to four cores for all likely problems sizes. This makes it competitive with FPGA-based systems for small molecule docking, and superior for proteinprotein docking.

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