// AI news · 2026-10-29 · NVIDIA
NVIDIA Enables Tensor Core Precision for ML Interatomic Potentials
NVIDIA demonstrates BF16x9 and TF32x3 Tensor Core precision methods on machine learning interatomic potentials, achieving up to 2.5x GEMM acceleration on Blackwell GPUs and 1.9x speedup on Ampere for key operations.
Published 2026-10-29 23:00 (Beijing time)Source NVIDIAAuto-summarised, fact-checked against source
01Summary
These methods maintain force accuracy and energy conservation, enabling faster simulations without sacrificing physical fidelity in large-scale molecular dynamics.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- BF16x9 achieves 2.2–2.5x GEMM acceleration on Blackwell GPUs.
- TF32x3 improves key GEMMs by 1.7–1.9x and full MD steps up to 1.5x on Ampere.
- TF32x3 maintains energy conservation and smooth potential energy in dynamics.
- Methods preserve FP32-level physical behavior during simulation.
03Source
Unlocking Tensor Core Performance for Machine Learning Interatomic Potentials
NVIDIA · published 2026-10-29 23:00 Beijing time
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