Mixed precision sampling of quantum states of matter
ORAL
Abstract
Monte Carlo simulations are widely used throughout all areas of science. In materials science, they provide an important framework to unravel the mechanisms that give rise to complex behavior and different quantum states of matter. The DCA++ code is a high-performance research application that solves quantum many-body, materials problems with a cutting edge quantum Monte Carlo based dynamic cluster approximation (DCA). Here we discuss how mixed precision arithmetics finds a natural home in statistical sampling based Monte Carlo, and how it is being used in DCA++ to boost performance on ORNL’s Summit supercomputer.
*This work was supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, Division of Materials Sciences and Engineering.
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Presenters
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Thomas Maier
- Computational Sciences and Engineering Division and Center for Nanophase Materials Sciences, Oak Ridge National Laboratory
- Oak Ridge National Laboratory
- Oak Ridge National Lab
- Center for Nanophase Materials Sciences,Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6164, USA and Computational Sciences and Engineering Division, Oak Ridge Nat
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory