On the Convergence Theory of Pipeline Gradient-based Analog In-memory Training
arXiv:2410.15155v3 Announce Type: replace
Abstract: Aiming to accelerate the training of large deep neural networks (DNN) in an energy-efficient way, analog in-memory computing (AIMC) emerges as a solution with immense potential. AIMC accelerator keep…