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cs.LG2026
Compaction-Aware Reinforcement Learning For Ascend Triton Kernel Generation
Chuansai Zhou, Yanlin Liu, Bingning Huang +7
Automatically generating high-performance kernels with LLM-based agents promises substantial gains in development efficiency, but two obstacles remain. First, while increasing mult…
cs.LG2026
CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training
Rezaul Karim, Austin Wen, Wang Zongzuo +3
The rapid growth in the size of large language models has necessitated the partitioning of computational workloads across accelerators such as GPUs, TPUs, and NPUs. However, these…