Communications of the ACM
Gordon Bell Prize Awarded for Materials Simulations That Achieve Quantum Accuracy at Scale
The ACM Gordon Bell Prize tracks the progress of parallel computing and rewards innovation in applying high-performance computing to challenges in science, engineering, and large-scale data analytics.
Credit: Association of Computing Machinery
A team of researchers from U.S. and Indian institutions was awarded the 2023 ACM Gordon Bell Prize for a materials-simulation framework that combines the accuracy provided by Quantum Many-Body (QMB) methods with the efficiency of Density-Functional Theory (DFT).
The team proposed three interconnected modules for their new method.
One was a methodological advance in inverse DFT (invDFT) linking QMB methods to DFT.
The second module was a machine-learned density functional trained with invDFT data, commensurate with quantum accuracy, which they dubbed MLXC.
The third was an adaptive higher-order spectral finite-element based DFT implementation that integrates MLXC with efficient solver strategies and supercomputing innovations in linear algebra, mixed-precision algorithms, and asynchronous compute-communication.
The award was presented at the International Conference for High-Performance Computing, Networking, Storage and Analysis (SC23).
From Association for Computing Machinery
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Abstracts Copyright © 2023 SmithBucklin, Washington, D.C., USA
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