most citedA Queueing Theoretic Perspective on Low-Latency LLM Inference with Variable Token Length

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cs.DC2025

Deadline-Aware Online Scheduling for LLM Fine-Tuning with Spot Market Predictions

Linggao Kong, Yuedong Xu, Lei Jiao +1

As foundation models grow in size, fine-tuning them becomes increasingly expensive. While GPU spot instances offer a low-cost alternative to on-demand resources, their volatile pri…

cs.DC2025

Diving into 3D Parallelism with Heterogeneous Spot Instance GPUs: Design and Implications

Yuxiao Wang, Yuedong Xu, Qingyang Duan +4

The rapid growth of large language models (LLMs) and the continuous release of new GPU products have significantly increased the demand for distributed training across heterogeneou…