10 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.LG2024
LAYUP: Asynchronous decentralized gradient descent with LAYer-wise UPdates
Cabrel Teguemne Fokam, Marcel Nieveler, Lukas König +3
The increasing size of deep learning models has made distributed training across multiple devices essential. Synchronous, centralized methods incur large communication and synchron…
cs.NE2024★ 10 cited
Language Modeling on a SpiNNaker 2 Neuromorphic Chip
Khaleelulla Khan Nazeer, Mark Schöne, Rishav Mukherji +4
As large language models continue to scale in size rapidly, so too does the computational power required to run them. Event-based networks on neuromorphic devices offer a potential…