2 papers
cond-mat.mtrl-sci2026
GPUMDkit: A User-Friendly Toolkit for GPUMD and NEP
Zihan Yan, Denan Li, Xin Wu +20
Machine-learned interatomic potentials have revolutionized molecular dynamics simulations by providing quantum-mechanical accuracy at empirical-potential speeds. The graphics proce…
cs.LG2024
Enabling High Data Throughput Reinforcement Learning on GPUs: A Domain Agnostic Framework for Data-Driven Scientific Research
Tian Lan, Huan Wang, Caiming Xiong +1
We introduce WarpSci, a domain agnostic framework designed to overcome crucial system bottlenecks encountered in the application of reinforcement learning to intricate environments…