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cs.DC2026
FlashCP: Load-Balanced Communication-Efficient Context Parallelism for LLM Training
Zheng Wang, Eric Liu, Linan Jiang +5
Context parallelism (CP) is essential for training large-scale, long-context language models, as it partitions sequences to reduce memory overhead. However, existing CP methods suf…
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…