most citedRAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required!

45 citations · 45 across the 1 of their papers we have counts for

collaborators

1 paper

cs.AR2023★ 45 cited

RAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required!

Tanner Andrulis, Joel S. Emer, Vivienne Sze

Processing-In-Memory (PIM) accelerators have the potential to efficiently run Deep Neural Network (DNN) inference by reducing costly data movement and by using resistive RAM (ReRAM…