Zobrazeno 1 - 10
of 268
pro vyhledávání: '"Kämpfe Thomas"'
Computationally challenging combinatorial optimization problems (COPs) play a fundamental role in various applications. To tackle COPs, many Ising machines and Quadratic Unconstrained Binary Optimization (QUBO) solvers have been proposed, which typic
Externí odkaz:
http://arxiv.org/abs/2410.14111
The concept of Nash equilibrium (NE), pivotal within game theory, has garnered widespread attention across numerous industries. Recent advancements introduced several quantum Nash solvers aimed at identifying pure strategy NE solutions (i.e., binary
Externí odkaz:
http://arxiv.org/abs/2408.04169
Autor:
Xu, Zhicheng, Liu, Che-Kai, Li, Chao, Mao, Ruibin, Yang, Jianyi, Kämpfe, Thomas, Imani, Mohsen, Li, Can, Zhuo, Cheng, Yin, Xunzhao
Rapid advancements in artificial intelligence have given rise to transformative models, profoundly impacting our lives. These models demand massive volumes of data to operate effectively, exacerbating the data-transfer bottleneck inherent in the conv
Externí odkaz:
http://arxiv.org/abs/2401.05708
Frequency multipliers, a class of essential electronic components, play a pivotal role in contemporary signal processing and communication systems. They serve as crucial building blocks for generating high-frequency signals by multiplying the frequen
Externí odkaz:
http://arxiv.org/abs/2312.17444
Autor:
Xu, Yixin, Xiao, Yi, Zhao, Zijian, Müller, Franz, Vardar, Alptekin, Gong, Xiao, George, Sumitha, Kämpfe, Thomas, Narayanan, Vijaykrishnan, Ni, Kai
Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats
Externí odkaz:
http://arxiv.org/abs/2306.01863
Autor:
Yin, Xunzhao, Huang, Qingrong, Müller, Franz, Deng, Shan, Vardar, Alptekin, De, Sourav, Jiang, Zhouhang, Imani, Mohsen, Zhuo, Cheng, Kämpfe, Thomas, Ni, Kai
In this work, we propose a ferroelectric FET(FeFET) time-domain compute-in-memory (TD-CiM) array as a homogeneous processing fabric for binary multiplication-accumulation (MAC) and content addressable memory (CAM). We demonstrate that: i) the XOR(XNO
Externí odkaz:
http://arxiv.org/abs/2209.11971
Autor:
Yin, Xunzhao, Müller, Franz, Huang, Qingrong, Li, Chao, Imani, Mohsen, Yang, Zeyu, Cai, Jiahao, Lederer, Maximilian, Olivo, Ricardo, Laleni, Nellie, Deng, Shan, Zhao, Zijian, Zhuo, Cheng, Kämpfe, Thomas, Ni, Kai
Content addressable memory (CAM) is widely used in associative search tasks for its highly parallel pattern matching capability. To accommodate the increasingly complex and data-intensive pattern matching tasks, it is critical to keep improving the C
Externí odkaz:
http://arxiv.org/abs/2203.07948
Autor:
Sünbül, Ayse, Lehninger, David, Pourjafar, Amir, Yang, Shouzhuo, Müller, Franz, Olivo, Ricardo, Kämpfe, Thomas, Seidel, Konrad, Eng, Lukas, Lederer, Maximilian
Publikováno v:
In Memories - Materials, Devices, Circuits and Systems August 2024 8
Autor:
Yin, Xunzhao, Müller, Franz, Laguna, Ann Franchesca, Li, Chao, Ye, Wenwen, Huang, Qingrong, Zhang, Qinming, Shi, Zhiguo, Lederer, Maximilian, Laleni, Nellie, Deng, Shan, Zhao, Zijian, Niemier, Michael, Hu, Xiaobo Sharon, Zhuo, Cheng, Kämpfe, Thomas, Ni, Kai
Deep random forest (DRF), which incorporates the core features of deep learning and random forest (RF), exhibits comparable classification accuracy, interpretability, and low memory and computational overhead when compared with deep neural networks (
Externí odkaz:
http://arxiv.org/abs/2110.02495
This paper reports the impacts of temperature variation on the inference accuracy of pre-trained all-ferroelectric FinFET deep neural networks, along with plausible design techniques to abate these impacts. We adopted a pre-trained artificial neural
Externí odkaz:
http://arxiv.org/abs/2103.03111