activity
20182026
most citedTowards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

30 citations · 54 across the 11 of their papers we have counts for

collaborators

11 papers

cs.DC2026

MakoXC: Rearchitecting DFT Exchange-Correlation with Matrix-Aligned and Knowledge-Organized Sparsity

Haozhi Han, Fusong Ju, Jing Bai +8

Density Functional Theory (DFT) is indispensable for materials science and drug discovery, yet the exchange--correlation (XC) evaluation remains a major bottleneck due to its cubic…

cs.AI2026

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…

physics.comp-ph2026

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…

physics.comp-ph2026

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…

physics.chem-ph20261 cited

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…

cs.DC2024

Matryoshka: Optimization of Dynamic Diverse Quantum Chemistry Systems via Elastic Parallelism Transformation

Tuowei Wang, Kun Li, Donglin Bai +6

AI infrastructures, predominantly GPUs, have delivered remarkable performance gains for deep learning. Conversely, scientific computing, exemplified by quantum chemistry systems, s…