Author

Ying Liu

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Preprint Aug 2026

Unlocking Multi-Component Bulk-Materials Molecular Dynamics with a Small-Footprint Machine Learning Interatomic Potential

Bulk materials, as opposed to nanomaterials, require molecular dynamics (MD) simulations on a large spatial scale (~10^9 atoms or more) to adequately capture their atomic-scale physical properties. Previously, the introduction of machine-learning interatomic potentials (MLIPs) has extended MD to this scale, but even si...

Yucheng Ouyang, Xin Chen, Ying Liu et al. · 0 citations

#artificial intelligence Preprint May 2026

KLineage: Recovering the Missing When of Kernel Optimization by Deoptimizing Experts

This work introduces KLineage, which learns this missing"when"knowledge from expert kernels: instead of relying on forward rollouts, KLineage walks expert implementations backward through validation-gated simplifications and reverses each accepted step into a reusable optimization skill.

Shuo-Ming Zhang, Qiu-Chun Yu, Rui-Yuan Xu et al. · 0 citations

Sep 2026

HIP-DFPT: Scalable Optimization of Irregular Workloads in Quantum Perturbation on GPU Clusters

Irregular workloads challenge GPUs with small tasks, unpredictable branching, and uneven load distribution. Quantum perturbation theory and Density Functional Theory (DFT) represent a prominent example, where such irregular patterns arise in large-scale simulations of materials and molecules. Despite recent efforts to...

Meng Wan, Hao Du, Jue Wang et al. · IEEE Transactions on Paralle... · 3 citations