The University of Michigan is collaborating with IBM to develop and deliver “data-centric” supercomputing systems designed to increase the pace of scientific discovery in fields as diverse as aircraft and rocket engine design, cardiovascular disease treatment, materials physics, climate modeling and cosmology.
The system is designed to enable high performance computing applications for physics to interact, in real time, with big data in order to improve scientists´ ability to make quantitative predictions. IBM´s systems use a GPU-accelerated, data-centric approach, integrating massive datasets seamlessly with high performance computing power, resulting in new predictive simulation techniques that promise to expand the limits of scientific knowledge.
Working with IBM, U-M researchers have designed a computing resource called ConFlux to enable high performance computing clusters to communicate directly and at interactive speeds with data-intensive operations.
Hosted at U-M, the project establishes a hardware and software ecosystem to enable large-scale data-driven modeling of complex physical problems, such as the performance of an aircraft engine, which consists of trillions of molecular interactions. ConFlux, funded by a grant from the National Science Foundation, aims to advance predictive modeling in several fields of computational science. IBM is providing servers and software solutions.