133 citations · 302 across the 21 of their papers we have counts for
10 papers · 1 filter
TAP-CAM: A Tunable Approximate Matching Engine based on Ferroelectric Content Addressable Memory
Chenyu Ni, Sijie Chen, Che-Kai Liu +8
Pattern search is crucial in numerous analytic applications for retrieving data entries akin to the query. Content Addressable Memories (CAMs), an in-memory computing fabric, direc…
A Remedy to Compute-in-Memory with Dynamic Random Access Memory: 1FeFET-1C Technology for Neuro-Symbolic AI
Xunzhao Yin, Hamza Errahmouni Barkam, Franz Müller +14
Neuro-symbolic artificial intelligence (AI) excels at learning from noisy and generalized patterns, conducting logical inferences, and providing interpretable reasoning. Comprising…
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…
MIMHD: Accurate and Efficient Hyperdimensional Inference Using Multi-Bit In-Memory Computing
Arman Kazemi, Mohammad Mehdi Sharifi, Zhuowen Zou +3
Hyperdimensional Computing (HDC) is an emerging computational framework that mimics important brain functions by operating over high-dimensional vectors, called hypervectors (HVs).…
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…
A Device Non-Ideality Resilient Approach for Mapping Neural Networks to Crossbar Arrays
Arman Kazemi, Cristobal Alessandri, Alan C. Seabaugh +3
We propose a technology-independent method, referred to as adjacent connection matrix (ACM), to efficiently map signed weight matrices to non-negative crossbar arrays. When compare…
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…