As part of a series aimed at sharing best practices in preparing applications for Aurora, Argonne National Laboratory is highlighting researchers’ efforts to optimize codes to run efficiently on graphics processing units.

Quantum Monte Carlo (QMC) methods are ideal candidates for the next generation of material-design tools, which target not only simple bulk properties but collective effects in strongly correlated materials such as magnetic ordering, phase transitions, and quantum coherence.

The post Preparing for Aurora: Bringing Quantum Materials Simulation Code to Exascale Machines appeared first on HPCwire.

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