6 citations · 22 across the 12 of their papers we have counts for
7 papers · 1 filter
Energy Efficient Dual Designs of FeFET-Based Analog In-Memory Computing with Inherent Shift-Add Capability
Zeyu Yang, Qingrong Huang, Yu Qian +3
In-memory computing (IMC) architecture emerges as a promising paradigm, improving the energy efficiency of multiply-and-accumulate (MAC) operations within DNNs by integrating the p…
FeBiM: Efficient and Compact Bayesian Inference Engine Empowered with Ferroelectric In-Memory Computing
Chao Li, Zhicheng Xu, Bo Wen +5
In scenarios with limited training data or where explainability is crucial, conventional neural network-based machine learning models often face challenges. In contrast, Bayesian i…
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…
HyCiM: A Hybrid Computing-in-Memory QUBO Solver for General Combinatorial Optimization Problems with Inequality Constraints
Yu Qian, Zeyu Yang, Kai Ni +3
Computationally challenging combinatorial optimization problems (COPs) play a fundamental role in various applications. To tackle COPs, many Ising machines and Quadratic Unconstrai…
Energy-Efficient Cryogenic Ternary Content Addressable Memory using Ferroelectric SQUID
Shamiul Alam, Simon Thomann, Shivendra Singh Parihar +4
Ternary content addressable memories (TCAMs) are useful for certain computing tasks since they allow us to compare a search query with a whole dataset stored in the memory array. T…
C-Nash: A Novel Ferroelectric Computing-in-Memory Architecture for Solving Mixed Strategy Nash Equilibrium
Yu Qian, Kai Ni, Thomas Kämpfe +2
The concept of Nash equilibrium (NE), pivotal within game theory, has garnered widespread attention across numerous industries. Recent advancements introduced several quantum Nash…
Low Power and Temperature-Resilient Compute-In-Memory Based on Subthreshold-FeFET
Yifei Zhou, Xuchu Huang, Jianyi Yang +4
Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as 'memory wall' issue.…