Toward on-chip acceleration of the backpropagation algorithm using nonvolatile memory.

By performing computation at the location of data, non-Von Neumann (VN) computing should provide power and speed benefits over conventional (e.g., VN-based) approaches to data-centric workloads such as deep learning. For the on-chip training of large-scale deep neural networks using nonvolatile memory (NVM) based synapses, success will require performance levels (e.g., deep neural network classifi...