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cs.DC2025
Collective Communication for 100k+ GPUs
Min Si, Pavan Balaji, Yongzhou Chen +36
The increasing scale of large language models (LLMs) necessitates highly efficient collective communication frameworks, particularly as training workloads extend to hundreds of tho…
cs.DC2025★ 1 cited
WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training
Zheng Wang, Anna Cai, Xinfeng Xie +9
In this work, we present WLB-LLM, a workLoad-balanced 4D parallelism for large language model training. We first thoroughly analyze the workload imbalance issue in LLM training and…
cs.DC2024
Context Parallelism for Scalable Million-Token Inference
Amy Yang, Jingyi Yang, Aya Ibrahim +6
We present context parallelism for long-context large language model inference, which achieves near-linear scaling for long-context prefill latency with up to 128 H100 GPUs across…