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Unlocking Tensor Core Performance for Machine Learning Interatomic Potentials
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Anoushka Bhutani

· 1 min read

EngineeringNVIDIA Technical Blog

Unlocking Tensor Core Performance for Machine Learning Interatomic Potentials

Atomistic simulations help researchers understand how molecules and materials behave, from chemical reactions and phase transitions to mechanical failure. These...

Atomistic simulations help researchers understand how molecules and materials behave, from chemical reactions and phase transitions to mechanical failure. These simulations come with a cost-accuracy trade-off. Quantum-mechanical methods such as density functional theory (DFT) can provide accurate energies and forces, but their computational cost often limits their use for large systems or long…

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This story was published by NVIDIA Technical Blog and written by Anoushka Bhutani. SyncAI.news shows a preview; the complete article is on the publisher's site.

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