1 citations · 2 across the 2 of their papers we have counts for
Showing cs.DCShow all
2 papers · 1 filter
cs.DC2026
Architecting for Hardware Diversity: Meta's End-to-End Co-Design for High-Performance AI Training on AMD GPUs
Haoyu Zhang, Arshad Rahman, Adnan Aziz +55
Meta deploys a heterogeneous fleet comprising NVIDIA GPUs, AMD GPUs, and proprietary MTIA accelerators to reduce costs and mitigate vendor lock-in. However, the extensive history o…
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…