4 papers
How Good Can Linear Models Be for Time-Series Forecasting?
Lang Huang, Jinglue Xu, Luke Darlow
Time-series forecasting research has been moving steadily toward larger architectures, from specialized transformers to general-purpose foundation models, on the assumption that ca…
Scaling Laws of Global Weather Models
Yuejiang Yu, Langwen Huang, Alexandru Calotoiu +1
Data-driven models are revolutionizing weather forecasting. To optimize training efficiency and model performance, this paper analyzes empirical scaling laws within this domain. We…
Error bounded compression for weather and climate applications
Langwen Huang, Luigi Fusco, Florian Scheidl +4
As the resolution of weather and climate simulations increases, the amount of data produced is growing rapidly from hundreds of terabytes to tens of petabytes. The huge size become…
CrossPipe: Towards Optimal Pipeline Schedules for Cross-Datacenter Training
Tiancheng Chen, Ales Kubicek, Langwen Huang +1
Training large language models (LLMs) now requires resources that exceed a single datacenter, making cross-datacenter strategies increasingly crucial. We present CrossPipe, a frame…