2 papers
cs.ET2025
HePGA: A Heterogeneous Processing-in-Memory based GNN Training Accelerator
Chukwufumnanya Ogbogu, Gaurav Narang, Biresh Kumar Joardar +3
Processing-In-Memory (PIM) architectures offer a promising approach to accelerate Graph Neural Network (GNN) training and inference. However, various PIM devices such as ReRAM, FeF…
cs.AR2024
Dataflow-Aware PIM-Enabled Manycore Architecture for Deep Learning Workloads
Harsh Sharma, Gaurav Narang, Janardhan Rao Doppa +2
Processing-in-memory (PIM) has emerged as an enabler for the energy-efficient and high-performance acceleration of deep learning (DL) workloads. Resistive random-access memory (ReR…