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A Sandia Nationwide Laboratories supercomputer simulation mannequin known as SNAP that quickly predicts the habits of billions of interacting atoms has captured the melting of diamond when compressed by excessive pressures and temperatures. At a number of million atmospheres, the inflexible carbon lattice of the toughest identified substance on Earth is proven in SNAP (Spectral Neighbor Evaluation Potential) simulations to crack, soften into amorphous carbon after which recrystallize. The work may help understanding of the inner construction of carbon-based exoplanets and have essential implications for nuclear fusion efforts that make use of capsules fabricated from polycrystalline diamond.
This multi-billion atom simulation of shockwave propagation into initially uncompressed diamond (blue) makes use of a high-accuracy SNAP mannequin from Sandia Nationwide Laboratories to foretell that the ultimate state (orange) is shaped by recrystallization of amorphous cracks (crimson) that take form within the gentle blue, inexperienced and yellow compressed materials.
Designing novel supplies and implications for large planets
“We are able to now examine the response of many supplies underneath the identical excessive pressures,” mentioned Sandia scientist Aidan Thompson, who originated SNAP. “Functions embrace planetary science questions — for instance, what sort of impression stress would have led to the formation of our moon. It additionally opens the door to design and manufacture of novel supplies at excessive circumstances.”
The impact of utmost pressures and temperatures on supplies is also essential for devising inside fashions of big planets. Highly effective DOE amenities like Sandia’s Z machine and Lawrence Livermore Nationwide Laboratory’s Nationwide Ignition Facility can recreate near-identical circumstances of those worlds in earthly experiments that provide close-up examinations of radically compressed supplies. However even these uniquely highly effective machines can’t pinpoint key microscopic mechanisms of change underneath these excessive circumstances, as a consequence of limitations in diagnostics on the degree of atoms.
“Solely pc simulations can do this,” mentioned Thompson.
Gordon Bell paper finalist is about ‘a micron-sized hunk of compressed diamond’
A technical paper describing the simulation was chosen as a finalist for the Gordon Bell prize, sponsored yearly by the Affiliation of Computing Equipment. The diamond-specific modeling, which took solely a day on the Summit supercomputer (the quickest within the U.S.) at Oak Ridge Nationwide Laboratory, was led by Prof. Ivan Oleynik on the College of South Florida. Along with Sandia and USF, the collaborative group additionally included software program builders on the Division of Vitality’s Nationwide Vitality Analysis Scientific Computing Heart and the NVIDIA Company.
The group’s simulations relied on SNAP, one of many main machine-learning descriptions of interatomic interactions, to mannequin and clear up an important drawback, mentioned Thompson.
“We created gigantic simulations of a micron-sized hunk of compressed diamond,” mentioned Thompson. “To do that, we monitor the movement of billions of atoms by repeatedly calculating the atomic forces over very many, exceedingly tiny, intervals of time.”
Machine-learning bridged with quantum mechanical calculations
SNAP used machine-learning and different knowledge science strategies to coach a surrogate mannequin that faithfully reproduced the proper atomic forces. These had been calculated utilizing high-accuracy quantum mechanical calculations, that are solely potential for methods containing a couple of hundred atoms. The surrogate mannequin was then scaled as much as predict forces and accelerations for methods containing billions of atoms. All native atomic buildings that emerged within the large-scale simulations had been well-represented within the small-scale coaching knowledge, a crucial situation for accuracy.
One other vital a part of the ultimate consequence was efficiency optimization of the software program to run effectively on GPU-based supercomputers like Summit, mentioned Thompson. “Since 2018, simply by bettering the software program, we’ve been capable of make the SNAP code over 30 occasions quicker, shortening the time for these sorts of simulations by 97%. On the identical time, every technology of {hardware} is extra highly effective than the final. Because of this, calculations which may have till lately taken a whole 12 months can now be run in a day on Summit.”
Run time shortened by 97 p.c
“Since supercomputer time is dear and extremely aggressive,” mentioned Thompson, “every shortening of SNAP’s run time saves cash and will increase the usefulness of the mannequin.”
Sandia researchers Stan Moore and Mitchell Wooden made essential contributions to the SNAP mannequin and the dramatic efficiency enhancements.
The optimized software program for operating SNAP on supercomputers is out there within the open supply distribution of Sandia’s LAMMPS (https://www.lammps.org/) molecular dynamics code. The Sandia FitSNAP (https://github.com/FitSNAP/FitSNAP) software program for constructing new SNAP fashions can also be publicly obtainable.
The primary model of SNAP was created in 2012 with help from Sandia’s Laboratory Directed Analysis and Improvement program. Software program enchancment has been supported constantly since 2017 by the DOE Exascale Computing Undertaking, a collaborative effort of the U.S. Division of Vitality Workplace of Science and the Nationwide Nuclear Safety Administration.
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