  We present a GPU-accelerated version of the real-space SPARC electronic
structure code for performing Kohn-Sham density functional theory calculations
within the local density and generalized gradient approximations. In
particular, we develop a modular math kernel based implementation for NVIDIA
architectures wherein the computationally expensive operations are carried out
on the GPUs, with the remainder of the workload retained on the CPUs. Using
representative bulk and slab examples, we show that GPUs enable speedups of up
to 6x relative to CPU-only execution, bringing time to solution down to less
than 30 seconds for a metallic system with over 14,000 electrons, and enabling
significant reductions in computational resources required for a given wall
time.
