Codesign Performance Prediction for Computational Physics
POC: Stephan Eidenbenz
Description: This LDRD DR project aims to build a capability to predict runtime of computational physics methods and codes on novel architectures. It has open-sourced the Simian Discrete event simulation engine.
Empowering the Expert: Machine Learning with User Intelligence
POC: Reid B. Porter
Information-Driven Materials Discovery and Design
POC: Turab Lookman
Next Generation Quantum Molecular Dynamics
POC: Anders M. Niklasson
Extreme Materials at Extreme Scale
POC: Tim Germann
Abstract: The objective of the Exascale Co-design Center for Materials in Extreme Environments (ExMatEx) is to establish the interrelationship among algorithms, system software, and hardware required to develop a multiphysics exascale simulation framework for modeling materials subjected to extreme mechanical and radiation environments. Such a simulation capability will play a key role in solving many of today’s most pressing problems, including producing clean energy, extending nuclear reactor lifetimes, and certifying the aging nuclear stockpile.
Hybrid Quantum-Classical Computing
POC: Rolando Somma
Description: The main goal of this project is to investigate and exploit the performance potential of physically realizable quantum annealers in the context of hard optimization problems.