133 citations · 473 across the 24 of their papers we have counts for
7 papers · 1 filter
Deep Random Forest with Ferroelectric Analog Content Addressable Memory
Xunzhao Yin, Franz Müller, Ann Franchesca Laguna +14
Deep random forest (DRF), which incorporates the core features of deep learning and random forest (RF), exhibits comparable classification accuracy, interpretability, and low memor…
In-Memory Nearest Neighbor Search with FeFET Multi-Bit Content-Addressable Memories
Arman Kazemi, Mohammad Mehdi Sharifi, Ann Franchesca Laguna +6
Nearest neighbor (NN) search is an essential operation in many applications, such as one/few-shot learning and image classification. As such, fast and low-energy hardware support f…
FeCAM: A Universal Compact Digital and Analog Content Addressable Memory Using Ferroelectric
Xunzhao Yin, Chao Li, Qingrong Huang +5
Ferroelectric field effect transistors (FeFETs) are being actively investigated with the potential for in-memory computing (IMC) over other non-volatile memories (NVMs). Content Ad…
A Hybrid FeMFET-CMOS Analog Synapse Circuit for Neural Network Training and Inference
Arman Kazemi, Ramin Rajaei, Kai Ni +3
An analog synapse circuit based on ferroelectric-metal field-effect transistors is proposed, that offers 6-bit weight precision. The circuit is comprised of volatile least signific…
Nonvolatile Spintronic Memory Cells for Neural Networks
Andrew W. Stephan, Qiuwen Lou, Michael Niemier +2
A new spintronic nonvolatile memory cell analogous to 1T DRAM with non-destructive read is proposed. The cells can be used as neural computing units. A dual-circuit neural network…
Application-level Studies of Cellular Neural Network-based Hardware Accelerators
Qiuwen Lou, Indranil Palit, Tang Li +3
As cost and performance benefits associated with Moore's Law scaling slow, researchers are studying alternative architectures (e.g., based on analog and/or spiking circuits) and/or…
Efficient Analog Circuits for Boolean Satisfiability
Xunzhao Yin, Behnam Sedighi, Melinda Varga +3
Efficient solutions to NP-complete problems would significantly benefit both science and industry. However, such problems are intractable on digital computers based on the von Neum…