13 citations · 35 across the 17 of their papers we have counts for
6 papers · 1 filter
LLM4LLM: Bridging Kernel Benchmarks and Real Deployment via Closed-Loop Agentic Optimization
Hui Zeng, Pengfei Yang, Yanxin Chen +2
Large language models have become increasingly capable agents for low-level code and kernel optimization, but isolated kernel benchmarks provide only a proxy for the deployment beh…
A Fixed-Point Neural Operator for Size- and Functional-Transferable Hamiltonian Prediction
Yunhong Lou, Xihang Yue, Xinran Wei +2
Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbitals, energy levels, and electronic-stru…
Accelerating Locality-Driven Integration in Quantum Chemistry with Block-Structured Matrix Multiplication
Xinran Wei, Yan Pan, Fusong Ju +8
Locality-driven integration is a pervasive computational pattern in quantum chemistry, arising whenever spatially localized basis functions interact through numerical quadrature or…
FusionRCG: Orchestrating Recursive Computation Graphs across GPU Memory Hierarchies
Yihong Zhang, Xinran Wei, Junshi Chen +4
Evaluating high-dimensional integrals via deep hierarchical recurrences is a dominant cost in quantum chemistry. While CPUs manage these efficiently, GPUs suffer a critical mismatc…
GPU Accelerated Minimal Auxiliary Basis Approach TDDFT for Large Organic Molecules
Zehao Zhou, Xiaojie Wu, Yanheng Li +5
We introduce a GPU-accelerated implementation of time-dependent density functional theory with the minimal auxiliary basis approach (TDDFT-risp) in GPU4PySCF, together with large s…
Scalable Machine Learning Force Fields for Macromolecular Systems Through Long-Range Aware Message Passing
Chu Wang, Lin Huang, Xinran Wei +4
Machine learning force fields (MLFFs) have revolutionized molecular simulations by providing quantum mechanical accuracy at the speed of molecular mechanical computations. However,…