2 papers
cs.DC2025
LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
Sheng Lin, Fangcheng Fu, Haoyang Li +5
With the breakthrough of Transformer-based pre-trained models, the demand for fine-tuning (FT) to adapt the base pre-trained models to downstream applications continues to grow, so…
cs.AR2024
Theseus: Exploring Efficient Wafer-Scale Chip Design for Large Language Models
Jingchen Zhu, Chenhao Xue, Yiqi Chen +13
The emergence of the large language model~(LLM) poses an exponential growth of demand for computation throughput, memory capacity, and communication bandwidth. Such a demand growth…