From the 1 of 10 linked papers with an AI index.
10 papers
MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training
Yikai Wang, Chuansai Zhou, Yuhang Zhou +10
Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substantial debugging overhead. In…
Adaptive Matrix Multiplication for Dynamic Shapes on Ascend NPUs
Yuhang Zhou, Jiang Peng, Qianyu Jiang +7
Matrix Multiplication (MatMul) faces a "generalization crisis" driven by highly dynamic tensor shapes. This crisis is particularly acute on Ascend NPUs, where explicitly controlled…
SmartSwap: Swap-Based Memory Optimization for LLM Training under Varying Operator Sequences
Zibo Wang, Yuhang Zhou, Zhibin Wang +13
The paper introduces SmartSwap, a swap‑based memory optimization framework that adapts to varying operator sequences in eager‑mode training of large language models, using a lightw…
PassNet: Scaling Large Language Models for Graph Compiler Pass Generation
Yiqun Liu, Yingsheng Wu, Ruqi Yang +11
Modern tensor compilers such as TorchInductor deliver substantial speedups on mainstream models, yet face a systematic performance ceiling on long-tail workloads -- our profiling s…
SSV: Sparse Speculative Verification for Efficient LLM Inference
Zhibin Wang, Ziyu Zhong, Nuo Shen +3
Speculative decoding and dynamic sparse attention are two complementary approaches for accelerating long-context LLM inference: the former amortizes target-model execution across m…
Chameleon: Adaptive Fault Tolerance for Distributed Training via Real-time Policy Selection
Yuhang Zhou, Zhibin Wang, Peng Jiang +12
Training large language models faces frequent interruptions due to various faults, demanding robust fault-tolerance. Existing backup-free methods, such as redundant computation, dy…