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ScaleAcross Explorer: Exploring Communication Optimization for Scale-Across AI Model Training
Minghao Li, Alicia Golden, Samuel Hsia +14
The rapid scaling of large language model training requires distributing GPU resources across multiple data center buildings and regions. We refer to such paradigm as "scale-across…
PRISM: Probabilistic Runtime Insights and Scalable Performance Modeling for Large-Scale Distributed Training
Alicia Golden, Michael Kuchnik, Samuel Hsia +4
Large model training beyond tens of thousands of GPUs is an uncharted territory. At such scales, disruptions to the training process are not a matter of if, but a matter of when --…
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation
Alicia Golden, Samuel Hsia, Fei Sun +8
As the development of large-scale Generative AI models evolve beyond text (1D) generation to include image (2D) and video (3D) generation, processing spatial and temporal informati…
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems
Samuel Hsia, Alicia Golden, Bilge Acun +5
Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high operational costs. Our ana…