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pro vyhledávání: '"spin‐orbit torque"'
Akademický článek
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Akademický článek
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Publikováno v:
Advanced Science, Vol 11, Iss 34, Pp n/a-n/a (2024)
Abstract Antiferromagnets are competitive candidates for the next generation of spintronic devices owing to their superiority in small‐scale and low‐power‐consumption devices. The electrical manipulation of the magnetization and exchange bias (
Externí odkaz:
https://doaj.org/article/e733f4eb8bfc49e280e36752e8bf2e21
Autor:
Leandro M. Giacomini Rocha, Mohamed Naeim, Guilherme Paim, Moritz Brunion, Priya Venugopal, Dragomir Milojevic, James Myers, Mustafa Badaroglu, Marian Verhelst, Julien Ryckaert, Dwaipayan Biswas
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 125-134 (2024)
High-performance edge artificial intelligence (Edge-AI) inference applications aim for high energy efficiency, memory density, and small form factor, requiring a design-space exploration across the whole stack—workloads, architecture, mapping, and
Externí odkaz:
https://doaj.org/article/226b40e97ae0451ba5bc686ec2cc116c
Autor:
Yuya Fujiwara, Takayuki Kawahara
Publikováno v:
IEEE Access, Vol 12, Pp 150962-150974 (2024)
To build Neural Networks (NNs) on edge devices, Binarized Neural Network (BNN) has been proposed on the software side, while Computing-in-Memory (CiM) architecture has been proposed on the hardware side. For use on CiM architecture-based BNN, Magneti
Externí odkaz:
https://doaj.org/article/9f62b4a18cf14024a7359545cb7cc2f8
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 13-21 (2024)
While magnetic random-access memories (MRAMs) are promising because of their nonvolatility, relatively fast speeds, and high endurance, there are major challenges in adopting them for the advanced technology nodes. One of the major challenges in scal
Externí odkaz:
https://doaj.org/article/c57ce292b48d402b8edde7ca486724fd
Akademický článek
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Autor:
Ran Zhang, Xiaohan Li, Mingkun Zhao, Caihua Wan, Xuming Luo, Shiqiang Liu, Yu Zhang, Yizhan Wang, Guoqiang Yu, Xiufeng Han
Publikováno v:
Advanced Science, Vol 11, Iss 23, Pp n/a-n/a (2024)
Abstract The incorporation of randomness into stochastic computing can provide ample opportunities for applications such as simulated annealing, non‐polynomial hard problem solving, and Bayesian neuron networks. In these cases, a considerable numbe
Externí odkaz:
https://doaj.org/article/f7239f6e61e449f0bedef811a2fbe77e
Autor:
Ao Du, Daoqian Zhu, Zhiyang Peng, Zongxia Guo, Min Wang, Kewen Shi, Kaihua Cao, Chao Zhao, Weisheng Zhao
Publikováno v:
Advanced Electronic Materials, Vol 10, Iss 6, Pp n/a-n/a (2024)
Abstract Antiferromagnets (AFM) hold significant promise as ideal candidates for high‐density and ultrafast memory applications. Electrical manipulation of exchange bias (EB) has emerged as an effective solution to integrate AFMs into magnetic memo
Externí odkaz:
https://doaj.org/article/2670174666034b7392bfa554ed41c80a
Autor:
Cen Wang, Guang Zeng, Xinyu Wen, Yuhui He, Wei Luo, Shiwei Chen, Xiaofei Yang, Shiheng Liang, Yue Zhang
Publikováno v:
Advanced Electronic Materials, Vol 10, Iss 6, Pp n/a-n/a (2024)
Abstract Stochasticity plays a significant role in the low‐power operation of a biological neural network. In an artificial neural network, stochasticity also contributes to critical functions such as the uncertainty quantification (UQ) for estimat
Externí odkaz:
https://doaj.org/article/80f441fd173342aa943b712ee6de373f