Zobrazeno 1 - 10
of 333
pro vyhledávání: '"Querlioz, D."'
Autor:
Esmanhotto, E., Hirtzlin, T., Castellani, N., Martin, S., Giraud, B., Andrieu, F., Nodin, J. F., Querlioz, D., Portal, J-M., Vianello, E.
Crossbar arrays of resistive memories (RRAM) hold the promise of enabling In-Memory Computing (IMC), but essential challenges due to the impact of device imperfection and device endurance have yet to be overcome. In this work, we demonstrate experime
Externí odkaz:
http://arxiv.org/abs/2203.01680
Publikováno v:
Phys. Rev. Applied 15, 034067 (2021)
Exploiting the physics of nanoelectronic devices is a major lead for implementing compact, fast, and energy efficient artificial intelligence. In this work, we propose an original road in this direction, where assemblies of spintronic resonators used
Externí odkaz:
http://arxiv.org/abs/2011.07885
Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons an
Externí odkaz:
http://arxiv.org/abs/2007.06092
In the field of Continual Learning, the objective is to learn several tasks one after the other without access to the data from previous tasks. Several solutions have been proposed to tackle this problem but they usually assume that the user knows wh
Externí odkaz:
http://arxiv.org/abs/2006.13772
Autor:
Riou, M., Torrejon, J., Garitaine, B., Araujo, F. Abreu, Bortolotti, P., Cros, V., Tsunegi, S., Yakushiji, K., Fukushima, A., Kubota, H., Yuasa, S., Querlioz, D., Stiles, M. D., Grollier, J.
Publikováno v:
Phys. Rev. Applied 12, 024049 (2019)
The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In this study,
Externí odkaz:
http://arxiv.org/abs/1905.02695
Autor:
Riou, M., Araujo, F. Abreu, Torrejon, J., Tsunegi, S., Khalsa, G., Querlioz, D., Bortolotti, P., Cros, V., Yakushiji, K., Fukushima, A., Kubota, H., Yuasa, S., Stiles, M. D., Grollier, J.
Fabricating powerful neuromorphic chips the size of a thumb requires miniaturizing their basic units: synapses and neurons. The challenge for neurons is to scale them down to submicrometer diameters while maintaining the properties that allow for rel
Externí odkaz:
http://arxiv.org/abs/1904.11236
Autor:
Talatchian, P., Romera, M., Tsunegi, S., Araujo, F. Abreu, Cros, V., Bortolotti, P., Trastoy, J., Yakushiji, K., Fukushima, A., Kubota, H., Yuasa, S., Ernoult, M., Vodenicarevic, D., Hirtzlin, T., Locatelli, N., Querlioz, D., Grollier, J.
Can we build small neuromorphic chips capable of training deep networks with billions of parameters? This challenge requires hardware neurons and synapses with nanometric dimensions, which can be individually tuned, and densely connected. While nanos
Externí odkaz:
http://arxiv.org/abs/1904.11240
Superparamagnetic tunnel junctions are nanostructures that auto-oscillate stochastically under the effect of thermal noise. Recent works showed that despite their stochasticity, such junctions possess a capability to synchronize to subthreshold volta
Externí odkaz:
http://arxiv.org/abs/1606.09211
Autor:
Mizrahi, A., Locatelli, N., Lebrun, R., Cros, V., Fukushima, A., Kubota, H., Yuasa, S., Querlioz, D., Grollier, J.
When fabricating magnetic memories, one of the main challenges is to maintain the bit stability while downscaling. Indeed, for magnetic volumes of a few thousand nm3, the energy barrier between magnetic configurations becomes comparable to the therma
Externí odkaz:
http://arxiv.org/abs/1605.06932
Autor:
Zhao, W.S., Portal, J.M., Kang, W., Moreau, M., Zhang, Y., Aziza, H., Klein, J.-O., Wang, Z.H., Querlioz, D., Deleruyelle, D., Bocquet, M., Ravelosona, D., Muller, C., Chappert, C.
Publikováno v:
In Journal of Parallel and Distributed Computing June 2014 74(6):2484-2496