GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent

Heesu Kim, Hanmin Park, Taehyun Kim +6

In this paper, we present GradPIM, a processing-in-memory architecture which accelerates parameter updates of deep neural networks training. As one of processing-in-memory techniqu…