Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

AuToDocK is a molecular docking application that consists of a genetic algorithm coupled with the Solis-Wets local-search method. Despite its wide usage, its power consumption on heterogeneous systems has not been evaluated extensively. In this work, we evaluate the energy efficiency of an OpenCL-accelerated version of AuToDocK that, along with the traditional Solis-Wets method, newly incorporates the ADADELTA gradient-based local search. Executions on a Nvidia V100 GPU yielded energy efficiency improvements of up to 297x (Solis-Wets) and 137x (ADADELTA) with respect to the original AuToDocK baseline.