A GPU-accelerated performance portable particle-grid based protein ligand molecular docking tool that can be used for virtual drug discovery compound screens based on a molecular recognition model, that analysis a three-dimensional model of an interaction between a protein and a small molecule (ligand).
Oak Ridge National Laboratory
molecular docking, performance portability, computational drug discovery, Leadership Computing platforms, GPU acceleration.
C, C++, Cuda, HIP, Kokkos
Git/SVN Repository URL
miniMDock can be used to evaluate the performance and portability of GPU-accelerated particle-grid based protein ligand docking programs on different computer architectures. These evaluations are especially relevant as facilities transition from petascale systems and prepare for upcoming exascale systems that will use a variety of GPU vendors such as NVIDIA and AMD. The miniapp targets heterogeneous systems, built with compute nodes containing multi-core CPUs accelerated by GPGPUs using performance portable programming models (Kokkos) that enables porting to different emerging systems with minimal efforts, vendor-specific programming models such as CUDA for NVIDIA GPUs, and HIP versions that can be applicable for AMD and NVIDIA GPUs.