11 citations · 11 across the 1 of their papers we have counts for
2 papers
cs.AR2026
ComFuse: Fusing Complex Memory-Intensive Subgraphs with Compute-Intensive Kernels For Modern GPU Architectures
Di Mu, Tengyuan Jin, Zhenkun Wang +6
Modern deep learning workloads increasingly comprise heterogeneous computation graphs that combine compute-intensive operators with memory-intensive subgraphs. Existing deep learni…
physics.comp-ph2024★ 11 cited
Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework
Xiaojie Wu, Qiming Sun, Zhichen Pu +11
We describe our contribution as industrial stakeholders to the existing open-source GPU4PySCF project (https: //github.com/pyscf/gpu4pyscf), a GPU-accelerated Python quantum chemis…