3 papers
cs.DC2026
SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation
Jihu Guo, Sitian Lu, Tenghui Ma +4
Agentic kernel optimization automates manual GPU kernel tuning via iterative generation, validation, and profiling with reasoning LLMs, casting the optimization task as feedback-gu…
cs.DC2026
ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism
Tenghui Ma, Jihu Guo, Wei Gao +4
Hybrid parallelism underpins large-scale LLM training across tens of thousands of GPUs. At such scale, hardware failures on individual devices lead to performance skew across devic…
cs.DC2025
OctoPipe: Reducing Pipeline Bubbles for Heterogeneous Models via Co-Optimizing Partitioning, Placement, and Scheduling
Jihu Guo, Tenghui Ma, Wei Gao +6
Pipeline parallelism is widely used to train large language models (LLMs). However, increasing heterogeneity in model architectures exacerbates pipeline bubbles, thereby reducing t…