3 papers
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.PF2024
DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads
Qidong Zhao, Hao Wu, Yuming Hao +4
Effective performance profiling and analysis are essential for optimizing training and inference of deep learning models, especially given the growing complexity of heterogeneous c…
cs.LG2022
Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing
Aditya Desai, Keren Zhou, Anshumali Shrivastava
Advancements in deep learning are often associated with increasing model sizes. The model size dramatically affects the deployment cost and latency of deep models. For instance, mo…