RAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required! - Tanner Andrulis; Joel S. Emer; Vivienne Sze (ISCA, 2023)

Architecture-Level Modeling of Photonic Deep Neural Network Accelerators. - Tanner Andrulis; Gohar Irfan Chaudhry; Vinith M. Suriyakumar; Joel S. Emer; Vivienne Sze (ISPASS, 2024)

CiMLoop: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool. - Tanner Andrulis; Joel S. Emer; Vivienne Sze (ISPASS, 2024)

Modeling Analog-Digital-Converter Energy and Area for Compute-In-Memory Accelerator Design. - Tanner Andrulis; Ruicong Chen; Hae-Seung Lee; Joel S. Emer; Vivienne Sze (CoRR, 2024)