In 2011, Gaussian, Inc., PGI, and NVIDIA embarked on a long-term project to enable Gaussian on GPGPUs using a directives-based approach. OpenACC has emerged as the de-facto standard to port complex programs to GPU accelerators. We'll discuss how we attacked some of the challenges involved in working with a large-scale, feature-rich application like Gaussian. This includes a number of PGI extensions to the OpenACC 2.0 standard that we believe will have a positive impact on other programs. To conclude, we'll present a sample of GPU-based performance improvements on a variety of theories and methods.
Quantum chemistry (QC)?that is, the application of quantum mechanics to molecular systems?has become an integral tool to most, if not all of chemical, biological, and general material sciences. In this session, we describe how we have achieved speed-ups of more than 10x by accelerating existing CPU-based implementations of two of the most prominent models of modern wave function-based QC?the RI-MP2 and CCSD(T) models?as well as their local correlation Divide-Expand-Consolidate (DEC) formulations?DEC-RI-MP2 and DEC-CCSD(T). The codes in question have been accelerated in the massively parallel and linear-scaling LSDalton program using the compiler directives of the OpenACC 2.0 standard. Examples illustrating the efficiency of the resulting (portable) OpenACC GPU port will be provided.