This work includes a consortium acquisition of a shared high-performance computing (HPC) instrument emphasizing HPC-based science and engineering with the benefit of "on-demand" capabilities. The instrument is a hybrid platform, integrating a state-of-the-art cluster computer with forward-looking, potentially exascale-oriented, GPU accelerator hardware that will enable progress in key STEM applications across a consortium of higher-educational partners with a research agenda that spans science disciplines.
The system?s high levels of responsiveness will be applied to systems modeling and identification for immunology, interactive drug pathway analysis, bio-molecular electrostatics, virtual earth modeling and data analysis, multi-scale environment modeling, adaptive real-time model data synthesis, interactive virtualized materials design, and studying fundamental physics of matter. In computer science, researchers and industry collaborators will use the instrument as a controlled, configurable facility with an advanced user base and application workload, driving forward research into abstractions for next-generation HPC environments, enhanced virtualization methodologies for large-scale HPC, and quantitatively experimenting in cloud/service paradigms at scale for HPC.
The acquisition will catalyze collaboration among scientists, engineers, computational science practitioners and computer scientists with research interests in - broadening the use of HPC for critical science and engineering problems - driving knowledge in earth science, life science, material science and basic physics - developing new, more engaging approaches to HPC - paving the way for a post-petascale HPC ecosystem spanning software to workforce skills - ere are extensive education and outreach activities planned to grow participation across institutional research communities as well as among local collaborators at community colleges, in K-12 education, and in community organizations.
The instrument will contribute to cyberinfrastructure in multiple ways and will be a valuable part of a broader public-private partnership enhancing computational science infrastructure and catalyzing high-tech innovation.
