X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs

1 code implementation • 3 Apr 2023 • Giacomo Pedretti, John Moon, Pedro Bruel, Sergey Serebryakov, Ron M. Roth, Luca Buonanno, Tobias Ziegler, Cong Xu, Martin Foltin, Paolo Faraboschi, Jim Ignowski, Catherine E. Graves

In this work, we focus on an overall analog-digital architecture implementing a novel increased precision analog CAM and a programmable network on chip allowing the inference of state-of-the-art tree-based ML models, such as XGBoost and CatBoost.

Experimentally realized memristive memory augmented neural network

no code implementations • 15 Apr 2022 • Ruibin Mao, Bo Wen, Yahui Zhao, Arman Kazemi, Ann Franchesca Laguna, Michael Neimier, X. Sharon Hu, Xia Sheng, Catherine E. Graves, John Paul Strachan, Can Li

Memory augmented neural network has been proposed to achieve the goal, but the memory module has to be stored in an off-chip memory due to its size.

One-Shot Learning