Hybrid CPU/GPU Integral Engine for Strong-Scaling Ab Initio Methods
We present a parallel integral algorithm for two-electron contributions occurring in Hartree–Fock and hybrid density functional theory that allows for a strong scaling parallelization on inhomogeneous compute clusters. With a particular focus on graphic processing units, we show that our approach allows an efficient use of CPUs and graphics processing units (GPUs) simultaneously, although the different architectures demand conflictive strategies in order to ensure efficient program execution. Furthermore, we present a general strategy to use large basis sets like quadruple-ζ split valence on GPUs and investigate the balance between CPUs and GPUs depending on l-quantum numbers of the corresponding basis functions. Finally, we present first illustrative calculations using a hybrid CPU/GPU environment and demonstrate the strong-scaling performance of our parallelization strategy also for pure CPU-based calculations.