6 citations · 21 across the 18 of their papers we have counts for
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cs.DC2025
KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads
Yue Guan, Yuanwei Fang, Keren Zhou +5
In this work, we propose KPerfIR, a novel multilevel compiler-centric infrastructure to enable the development of customizable, extendable, and portable profiling tools tailored fo…
cs.DC2024
Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU Reconfiguration
Tianyu Wang, Sheng Li, Bingyao Li +6
Continuous learning (CL) has emerged as one of the most popular deep learning paradigms deployed in modern cloud GPUs. Specifically, CL has the capability to continuously update th…
cs.DC2021★ 4 cited
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core
Yuke Wang, Boyuan Feng, Yufei Ding
Over the most recent years, quantized graph neural network (QGNN) attracts lots of research and industry attention due to its high robustness and low computation and memory overhea…