Heterogeneous Manycore Architectures Enabled by Processing-in-Memory for Deep Learning: From CNNs to GNNs: (ICCAD Special Session Paper)

Resistive random-access memory (ReRAM)-based processing-in-memory (PIM) architectures have recently become a popular architectural choice for deep-learning applications. ReRAM-based architectures can accelerate inferencing and training of deep learning algorithms and are more energy efficient compared to traditional GPUs. However, these architectures have various limitations that affect the model ...