During the past few decades, computational simulation has become the “Third Pillar” of science, in addition to theory and experimentation. A major revolution taking place in High Performance Computing (HPC) today is the increasing use of machine learning to complement simulation. This project is providing researchers in computational science and engineering fields with access to state-of-the-art GPU-accelerated hardware and software resources. The choice of resources was motivated by the requirements of science drivers that address important societal and national problems in the areas of renewable energy, advanced manufacturing, advanced materials, electric power systems, cybersecurity, and quantum computing using simulation and/or machine learning. The new hardware is integrated with the existing campus HPC cluster. The hardware is shared with the broader academic research community through participation in the Open Science Grid. In addition to providing a valuable resource for faculty, the augmented HPC cluster is available for use by students for projects related to their thesis and dissertation work as well as for class projects. The software stack on the campus HPC cluster reflects that available on NSF supercomputer systems with similar architectures. Student researchers provide assistance with operation and maintenance of the cluster, thus equipping them with skills needed for future careers in HPC and large-scale machine learning fields. Expected outcomes of the project include the following: 1) increased use of HPC across disciplines, 2) improvement in faculty and student skills in using state-of-the art HPC technologies, and 3) increased rate of producing research results and publications.