33 citations · 35 across the 5 of their papers we have counts for
3 papers
cs.PF2024
HeteGen: Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices
Xuanlei Zhao, Bin Jia, Haotian Zhou +3
In recent times, the emergence of Large Language Models (LLMs) has resulted in increasingly larger model size, posing challenges for inference on low-resource devices. Prior approa…
cs.DC2023★ 33 cited
Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency
Ziming Liu, Shenggan Cheng, Haotian Zhou +1
Large-scale language models have become increasingly challenging and expensive to train. Among various methods addressing this issue, Pipeline Parallelism has been widely employed…
cs.DC2023★ 1 cited
ATP: Adaptive Tensor Parallelism for Foundation Models
Shenggan Cheng, Ziming Liu, Jiangsu Du +1
Foundation models have impressive performance and generalization capabilities across a wide range of applications. The increasing size of the models introduces great challenges for…