10 citations · 23 across the 9 of their papers we have counts for
4 papers · 1 filter
FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression
Zhenheng Tang, Xueze Kang, Yiming Yin +11
To alleviate hardware scarcity in training large deep neural networks (DNNs), particularly large language models (LLMs), we present FusionLLM, a decentralized training system desig…
BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems
Yuxin Wang, Yuhan Chen, Zeyu Li +11
Serving systems for Large Language Models (LLMs) are often optimized to improve quality of service (QoS) and throughput. However, due to the lack of open-source LLM serving workloa…
Fault-Tolerant Hybrid-Parallel Training at Scale with Reliable and Efficient In-memory Checkpointing
Yuxin Wang, Xueze Kang, Shaohuai Shi +8
To efficiently scale large model (LM) training, researchers transition from data parallelism (DP) to hybrid parallelism (HP) on GPU clusters, which frequently experience hardware a…
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs
Zhenheng Tang, Yuxin Wang, Xin He +8
The rapid growth of memory and computation requirements of large language models (LLMs) has outpaced the development of hardware, hindering people who lack large-scale high-end GPU…