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 has been used in DCA++ to significantly boost performance on ORNL’s Titan and Summit supercomputers.