5 citations · 10 across the 8 of their papers we have counts for
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cs.DC2025
FAST: An Efficient Scheduler for All-to-All GPU Communication
Yiran Lei, Dongjoo Lee, Liangyu Zhao +9
All-to-All(v) communication is a critical primitive in modern machine learning workloads, particularly mixture-of-experts (MoE) models. Unfortunately, efficient scheduling is chall…
cs.DC2024★ 1 cited
NanoFlow: Towards Optimal Large Language Model Serving Throughput
Kan Zhu, Yufei Gao, Yilong Zhao +13
Large Language Models (LLMs) have resulted in a surging demand for planet-scale serving systems, where tens of thousands of GPUs continuously serve hundreds of millions of users. C…
cs.DC2023
Efficient All-to-All Collective Communication Schedules for Direct-Connect Topologies
Prithwish Basu, Liangyu Zhao, Jason Fantl +3
The all-to-all collective communications primitive is widely used in machine learning (ML) and high performance computing (HPC) workloads, and optimizing its performance is of inte…