PIM-DL: Boosting DNN Inference on Digital Processing In-Memory Architectures via Data Layout Optimizations

Digital processing in-memory (DPIM) provides very low overhead, highly parallel computation in conventional memory, which significantly accelerates data-intensive workloads like deep neural networks (DNNs). DPIM-based DNN accelerators require that data be properly laid out to make the best use of the available in-memory operations. However, existing DPIM accelerators tend to optimize for a particu...