Communications of the ACM
Project Combines Modeling and Machine Learning
Turbulence simulations for a vortex such as a tornado or galaxy.
Credit: Karthik Duraisamy / University of Michigan
The University of Michigan has received a $2.42 million grant from the U.S. National Science Foundation for ConFlux, a new computing resource that will enable supercomputer simulations to interface with large datasets while running. In addition, UMich will provide $1.04 million toward the project, which will begin with the construction of the new Center for Data-Driven Computational Physics, supporting the fields of aerodynamics, climate science, cosmology, materials science, and cardiovascular research.
ConFlux will enhance traditional physics-based computer models with big data techniques and specialized supercomputing nodes matched to the needs of data-intensive operations, the university says. "ConFlux will be a unique facility specifically designed for physical modeling using massive volumes of data," says UMich professor Barzan Mozafari.
ConFlux will use machine-learning algorithms to create more reliable models trained with a combination of scaled-down models and observational and experimental data. The complex will focus on five major areas of study: cardiovascular disease; turbulence; clouds, rainfall, and climate; dark matter and dark energy; and material property prediction.
From HPC Wire
View Full Article
Abstracts Copyright © 2015 Information Inc., Bethesda, Maryland, USA
No entries found