Here, we present a different approach to improving the efficiency of the translational MC method. We describe the design, implementation, and validation of a new version of the standard MC/MD algorithm within the AMBER simulation code that utilizes a parallel MC algorithm implemented on graphical processing units (GPUs), resulting in speedups of roughly 10-to 1000-fold over the original MC/MD algorithm. The present method combines an MC method that allows multiple moves to be tried in parallel while still sampling configurations from the canonical distribution, with GPU acceleration of key bottleneck steps in the algorithm.