NSF Award
2320649
This award supports the acquisition of a specialized high-performance computing (HPC) cluster with state-of-the-art graphical processing units (GPUs) that offer unique capabilities compared to existing resources. The instrument will benefit hundreds of researchers within the Princeton community, external collaborators, and program participants, accelerating scientific discoveries with beneficial impacts on sustainability and human health. The instrument will catalyze frontier research across diverse disciplines, such as chemistry, chemical engineering, computer science, geophysics, mechanical engineering, neuroscience, plasma physics, and psychology, to unravel complex phenomena and pioneer transformative solutions to global challenges. In particular, the system supports research in the design of new materials for healthcare and sustainable-energy solutions, a deepening of our understanding of complex chemistry and physics, development of low-cost imaging systems for medicine and sensing, large-scale computations and analyses related to neuroscience, and more. Additionally, the instrument will foster education and utilization of high-performance GPUs through software dissemination and broadly accessible training programs. Major initiatives include an annual GPU Hackathon with NVIDIA, summer research programs for underrepresented undergraduate students and formerly incarcerated youth, engagement with an accelerator program for development and launching of startups led by students, and GPU-related workshops. These activities will cultivate exceptionally strong and well-prepared candidates for technical positions in industry, national labs, and academia.<br/> <br/>The instrument will feature 10 computing nodes, each with AMD Genoa CPUs and NVIDIA H100 GPUs. Importantly, the H100s offer enhanced asynchronous execution and substantial speedups over current A100s (e.g., 6x on Tensor Cores, 7x on DPX instructions, 2-8x on AI model training, and 30x on AI inference). With these GPUs, Princeton researchers and collaborators will leverage machine learning and high-speed calculations to achieve remarkable progress in their respective fields. By increasing throughput of molecular simulations, the machine will dramatically accelerate work flows for computationally guided design of novel catalytic materials, such as durable enzymes and polymer-MOF composites. GPU acceleration will yield pioneering ab initio-based descriptions of molecular and interfacial phenomena. The machine will also enable critical software developments towards efficiently mapping the earth’s interior, advancing inexpensive alternatives to medical magnetic resonance imaging, real-time mitigation strategies for fusion reactor control, and modeling complex combustion systems. Increased computing capabilities will support the design of novel nanophotonic imagers that unlock new applications in medicine or as optical diagnostics. The machine will further bolster high-throughput quantitative characterization to inform the neurological underpinnings of social communication and reward-seeking in animal models.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
