Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Daniels, Matthew W."'
Autor:
Yousuf, Osama, Hoskins, Brian, Ramu, Karthick, Fream, Mitchell, Borders, William A., Madhavan, Advait, Daniels, Matthew W., Dienstfrey, Andrew, McClelland, Jabez J., Lueker-Boden, Martin, Adam, Gina C.
Artificial neural networks have advanced due to scaling dimensions, but conventional computing faces inefficiency due to the von Neumann bottleneck. In-memory computation architectures, like memristors, offer promise but face challenges due to hardwa
Externí odkaz:
http://arxiv.org/abs/2404.15621
Autor:
Pocher, Liam A., Adeyeye, Temitayo N., Gibeault, Sidra, Talatchian, Philippe, Ebels, Ursula, Lathrop, Daniel P., McClelland, Jabez J., Stiles, Mark D., Madhavan, Advait, Daniels, Matthew W.
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing qualitatively accurate analog dynamics of these devices will be importa
Externí odkaz:
http://arxiv.org/abs/2403.11988
Autor:
Gibeault, Sidra, Adeyeye, Temitayo N., Pocher, Liam A., Lathrop, Daniel P., Daniels, Matthew W., Stiles, Mark D., McClelland, Jabez J., Borders, William A., Ryan, Jason T., Talatchian, Philippe, Ebels, Ursula, Madhavan, Advait
Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of probabilistic computing techniques. Augmenting an SMTJ with electronic circuits, to convert the random telegraph fluctu
Externí odkaz:
http://arxiv.org/abs/2312.13171
Autor:
Borders, William A., Madhavan, Advait, Daniels, Matthew W., Georgiou, Vasileia, Lueker-Boden, Martin, Santos, Tiffany S., Braganca, Patrick M., Stiles, Mark D., McClelland, Jabez J., Hoskins, Brian D.
Publikováno v:
Phys. Rev. Applied 22, 014057 (2024)
The increasing scale of neural networks needed to support more complex applications has led to an increasing requirement for area- and energy-efficient hardware. One route to meeting the budget for these applications is to circumvent the von Neumann
Externí odkaz:
http://arxiv.org/abs/2312.06446
Autor:
Cenker, John, Ovchinnikov, Dmitry, Yang, Harvey, Chica, Daniel G., Zhu, Catherine, Cai, Jiaqi, Diederich, Geoffrey, Liu, Zhaoyu, Zhu, Xiaoyang, Roy, Xavier, Cao, Ting, Daniels, Matthew W., Chu, Jiun-Haw, Xiao, Di, Xu, Xiaodong
The magnetic tunnel junction (MTJ) is a backbone device for spintronics. Realizing next generation energy efficient MTJs will require operating mechanisms beyond the standard means of applying magnetic fields or large electrical currents. Here, we de
Externí odkaz:
http://arxiv.org/abs/2301.03759
Autor:
Yousuf, Osama, Hossen, Imtiaz, Daniels, Matthew W., Lueker-Boden, Martin, Dienstfrey, Andrew, Adam, Gina C.
Data-driven modeling approaches such as jump tables are promising techniques to model populations of resistive random-access memory (ReRAM) or other emerging memory devices for hardware neural network simulations. As these tables rely on data interpo
Externí odkaz:
http://arxiv.org/abs/2211.15925
Autor:
Goodwill, Jonathan M., Prasad, Nitin, Hoskins, Brian D., Daniels, Matthew W., Madhavan, Advait, Wan, Lei, Santos, Tiffany S., Tran, Michael, Katine, Jordan A., Braganca, Patrick M., Stiles, Mark D., McClelland, Jabez J.
Publikováno v:
Physical Review Applied, 18(1) 014039 (2022)
The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include
Externí odkaz:
http://arxiv.org/abs/2112.09159
Autor:
Marković, Danijela, Daniels, Matthew W., Sethi, Pankaj, Kent, Andrew D., Stiles, Mark D., Grollier, Julie
We show analytically using a macrospin approximation that easy-plane spin Hall nano-oscillators excited by a spin-current polarized perpendicularly to the easy-plane have phase dynamics analogous to that of Josephson junctions. Similarly to Josephson
Externí odkaz:
http://arxiv.org/abs/2110.06737
Autor:
Talatchian, Philippe, Daniels, Matthew W., Madhavan, Advait, Pufall, Matthew R., Jué, Emilie, Rippard, William H., McClelland, Jabez J., Stiles, Mark D.
Publikováno v:
Phys. Rev. B 104, 054427 (2021)
Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling SMTJs gives rise to collective behavior that could be useful for cognitive computing. We use
Externí odkaz:
http://arxiv.org/abs/2106.03604
Autor:
Vakili, Hamed, Sakib, Mohammad Nazmus, Ganguly, Samiran, Stan, Mircea, Daniels, Matthew W., Madhavan, Advait, Stiles, Mark D., Ghosh, Avik W.
Race logic is a relative timing code that represents information in a wavefront of digital edges on a set of wires in order to accelerate dynamic programming and machine learning algorithms. Skyrmions, bubbles, and domain walls are mobile magnetic co
Externí odkaz:
http://arxiv.org/abs/2005.10704