203 citations · 593 across the 26 of their papers we have counts for
4 papers · 1 filter
Predicting Weather Uncertainty with Deep Convnets
Peter Grönquist, Tal Ben-Nun, Nikoli Dryden +4
Modern weather forecast models perform uncertainty quantification using ensemble prediction systems, which collect nonparametric statistics based on multiple perturbed simulations.…
Asynchronous Decentralized SGD with Quantized and Local Updates
Giorgi Nadiradze, Amirmojtaba Sabour, Peter Davies +2
Decentralized optimization is emerging as a viable alternative for scalable distributed machine learning, but also introduces new challenges in terms of synchronization costs. To t…
The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters
Daning Cheng, Hanping Zhang, Fen Xia +2
To gain a better performance, many researchers put more computing resource into an application. However, in the AI area, there is still a lack of a successful large-scale machine l…
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
Shigang Li, Tal Ben-Nun, Salvatore Di Girolamo +2
Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself. Traditional synch…