Modeling of Multi-scale Physical Systems
The mission of the Center for Data-Driven Computational Physics is to usher in the future of large-scale, data-driven modeling of multi-scale physical systems. We focus on data-driven solutions to these problems using high performance computing clusters. However, the interaction of high performance computing for physics with large-scale data is itself a challenging problem, meriting new hardware configurations, software, and computational methods. The Center will respond to this challenge via the ConFlux facility, conceived by MICDE faculty and hosted by ARC-TS.
Improving collaboration on large datasets
The Center for Network and Storage-Enabled Collaborative Computational Science seeks to address the challenges of extracting scientific results collaboratively from large, distributed or diverse data. Included in the Center is the NSF-funded OSiRIS project, a collaborative, multi-university venture led by MICDE faculty, and hosted by ARC-TS.
IBM is showcasing the current research developed with ConFlux, our ground-breaking cluster that uses IBM’s HPC and storage technology to enable scientists to draw on huge volumes of bid data and use machine learning…
From the Cosmic Frontier to CERN, New Platform Stitches Together Global Science Efforts SLATE will enable creation of new platforms for collaborative science Today’s most ambitious scientific quests — from…
Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided The Ph.D. in Scientific Computing is open to all Ph.D. students who will make…
MICDE Associate Director Siqian Shen has been selected to receive an Early Career Award for the Department of Energy Office of Science by the DoE Office of Advanced Scientific Computing Research….