# Dynamic Tensor Rematerialization will be at ICLR 2021

In the paper, we proved that at a linear feedforward setting, we can train a model under $\Omega (n)$ memory budget with only $\mathcal{O}(N)$ additional forward operator computations, which is a very small overhead and competitive to the state-of-the-art implementation of checkpointing (Checkmate, Jain et al.) as well as to checkpointing implementation by human experts.