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A Co-design view of Compute in-Memory with Non-Volatile Elements for
  Neural Networks

A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks

3 June 2022
W. Haensch
A. Raghunathan
Kaushik Roy
B. Chakrabarti
C. Phatak
Cheng Wang
Supratik Guha
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Papers citing "A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks"

2 / 2 papers shown
Title
Towards Efficient In-memory Computing Hardware for Quantized Neural
  Networks: State-of-the-art, Open Challenges and Perspectives
Towards Efficient In-memory Computing Hardware for Quantized Neural Networks: State-of-the-art, Open Challenges and Perspectives
O. Krestinskaya
Li Zhang
K. Salama
6
7
0
08 Jul 2023
Neural Network Training with Asymmetric Crosspoint Elements
Neural Network Training with Asymmetric Crosspoint Elements
M. Onen
Tayfun Gokmen
T. Todorov
T. Nowicki
Jesús A. del Alamo
J. Rozen
W. Haensch
Seyoung Kim
26
19
0
31 Jan 2022
1