Parallel Implementation of Density Functional Theory Methods in the Quantum Interaction Computational Kernel Program

We
present the details of a graphics processing unit (GPU) capable
exchange correlation (XC) scheme integrated into the open source QUantum
Interaction Computational Kernel (QUICK) program. Our implementation
features an octree based numerical grid point partitioning scheme,
GPU enabled grid pruning and basis and primitive function prescreening,
and fully GPU capable XC energy and gradient algorithms. Benchmarking
against the CPU version demonstrated that the GPU implementation is
capable of delivering an impressive performance while retaining excellent
accuracy. For small to medium size protein/organic molecular systems,
the realized speedups in double precision XC energy and gradient computation
on a NVIDIA V100 GPU were 60–80-fold and 140–500-fold,
respectively, as compared to the serial CPU implementation. The acceleration
gained in density functional theory calculations from a single V100
GPU significantly exceeds that of a modern CPU with 40 cores running
in parallel.