Zobrazeno 1 - 10
of 177
pro vyhledávání: '"Jacques-Olivier Klein"'
Autor:
Tifenn Hirtzlin, Bogdan Penkovsky, Marc Bocquet, Jacques-Olivier Klein, Jean-Michel Portal, Damien Querlioz
Publikováno v:
IEEE Access, Vol 7, Pp 76394-76403 (2019)
Binarized neural networks, a recently discovered class of neural networks with minimal memory requirements and no reliance on multiplication, are a fantastic opportunity for the realization of compact and energy efficient inference hardware. However,
Externí odkaz:
https://doaj.org/article/623e78b86a784051853722cbce36963c
Autor:
Christopher H. Bennett, Vivek Parmar, Laurie E. Calvet, Jacques-Olivier Klein, Manan Suri, Matthew J. Marinella, Damien Querlioz
Publikováno v:
IEEE Access, Vol 7, Pp 73938-73953 (2019)
Recently, a Cambrian explosion of a novel, non-volatile memory (NVM) devices known as memristive devices have inspired effort in building hardware neural networks that learn like the brain. Early experimental prototypes built simple perceptrons from
Externí odkaz:
https://doaj.org/article/47533fa00ed34d889501fb275d953415
Autor:
Tifenn Hirtzlin, Marc Bocquet, Bogdan Penkovsky, Jacques-Olivier Klein, Etienne Nowak, Elisa Vianello, Jean-Michel Portal, Damien Querlioz
Publikováno v:
Frontiers in Neuroscience, Vol 13 (2020)
The brain performs intelligent tasks with extremely low energy consumption. This work takes its inspiration from two strategies used by the brain to achieve this energy efficiency: the absence of separation between computing and memory functions and
Externí odkaz:
https://doaj.org/article/dbd1743fa64545fea508526d5b5e607c
Autor:
Zhenyi Zheng, Dafiné Ravelosona, Jinkai Wang, Jacques-Olivier Klein, Kun Zhang, Weisheng Zhao, Zhizhong Zhang, Yue Zhang, Guanda Wang
Publikováno v:
IEEE Electron Device Letters. 42:621-624
Ultrafast current-driven domain wall (DW) motions have been realized in ferrimagnetic (FiM) nanowires. However, the FiM dynamics can be significantly affected by the Joule-heating. In this work, we propose a highly efficient XNOR logic gate by proper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93431e3746a4495f0096fad92c77d0ad
https://doi.org/10.1109/led.2021.3062382
https://doi.org/10.1109/led.2021.3062382
Autor:
Etienne Nowak, Damien Querlioz, Marc Bocquet, Axel Laborieux, Atreya Majumdar, Elisa Vianello, Jean-Michel Portal, Tifenn Hirtzlin, Jacques-Olivier Klein
Publikováno v:
IEEE Transactions on Electron Devices
IEEE Transactions on Electron Devices, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2021, 68 (10), pp.4925-4932. ⟨10.1109/TED.2021.3108479⟩
The implementation of current deep learning training algorithms is power-hungry, due to data transfer between memory and logic units. Oxide-based resistive random access memories (RRAMs) are outstanding candidates to implement in-memory computing, wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edcbfdd9a7b73660ad52cf15830ef24e
https://hal.science/hal-03372056/document
https://hal.science/hal-03372056/document
Autor:
Weisheng Zhao, Mengxing Wang, Haochang Zhou, Zhaohao Wang, Jacques-Olivier Klein, Wenlong Cai, Daoqian Zhu
Publikováno v:
IEEE Electron Device Letters. 40:726-729
We propose a toggle spin torques magnetic random access memory (TST-MRAM) for ultrafast computing. The write operation of the TST-MRAM is achieved by applying two currents to the MTJ and a heavy metal layer, respectively, in a toggle-like manner. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c85901b17709751a8f8ddef7dd61c1e3
https://doi.org/10.1109/led.2019.2907063
https://doi.org/10.1109/led.2019.2907063
Autor:
Zhizhong Zhang, Dafiné Ravelosona, Jacques-Olivier Klein, Yue Zhang, Zhenyi Zheng, Weisheng Zhao, Kun Zhang, Guanda Wang, Jinkai Wang, Youguang Zhang
Publikováno v:
IEEE Transactions on Electron Devices
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2019, 66 (5), pp.2431-2436. ⟨10.1109/TED.2019.2906932⟩
IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers, 2019, 66 (5), pp.2431-2436. ⟨10.1109/TED.2019.2906932⟩
As the basic storage unit of spin transfer torque magnetic random-access memory (STT-MRAM), the perpendicular magnetic anisotropy (PMA) magnetic tunnel junction (MTJ) has been extensively studied in recent years. Lowering the critical switching curre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea833678c719f327cee0e74da799811f
https://doi.org/10.1109/ted.2019.2906932
https://doi.org/10.1109/ted.2019.2906932
Autor:
Marc Bocquet, Damien Querlioz, Jacques-Olivier Klein, Elisa Vianello, Etienne Nowak, Jean-Michel Portal, Axel Laborieux, Tifenn Hirtzlin
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers
IEEE Transactions on Circuits and Systems I: Regular Papers, IEEE, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, IEEE, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020, pp.1-10. ⟨10.1109/TCSI.2020.3031627⟩
The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a significant lead for reducing the energy consumption of artificial intelligence. To achieve maximum energy effi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aca5a159c791b6a8326502c6aa7983ce
https://hal.archives-ouvertes.fr/hal-02983778/document
https://hal.archives-ouvertes.fr/hal-02983778/document
Autor:
Bogdan Penkovsky, Jean-Michel Portal, Jacques-Olivier Klein, Elisa Vianello, Etienne Nowak, Damien Querlioz, Marc Bocquet, Tifenn Hirtzlin
Publikováno v:
2020 Design, Automation & Test in Europe Conference & Exhibition (DATE)
2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), Mar 2020, Grenoble, France. pp.690-695, ⟨10.23919/DATE48585.2020.9116439⟩
DATE
2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), Mar 2020, Grenoble, France. pp.690-695, ⟨10.23919/DATE48585.2020.9116439⟩
DATE
The advent of deep learning has considerably accelerated machine learning development. The deployment of deep neural networks at the edge is however limited by their high memory and energy consumption requirements. With new memory technology availabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b67fab47b9c5c2da0f64e2d5e0656de
https://hal.science/hal-03218970/file/DATE2020_Penkovsky.pdf
https://hal.science/hal-03218970/file/DATE2020_Penkovsky.pdf
Autor:
E. Nowak, J-M. Portal, Jacques-Olivier Klein, Marc Bocquet, Damien Querlioz, E. Vianello, Maxence Ernoult, Tifenn Hirtzlin
Publikováno v:
2019 IEEE International Electron Devices Meeting (IEDM)
2019 IEEE International Electron Devices Meeting (IEDM), Dec 2019, San Francisco, United States. ⟨10.1109/IEDM19573.2019.8993555⟩
2019 IEEE International Electron Devices Meeting (IEDM), Dec 2019, San Francisco, United States. ⟨10.1109/IEDM19573.2019.8993555⟩
International audience; Exploiting the analog properties of RRAM cells for learning is a compelling approach, but which raises important challenges in terms of CMOS overhead, impact of device imperfections and device endurance. In this work, we inves
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ab89b152aed5757e2aa5a871c496353
https://doi.org/10.1109/iedm19573.2019.8993555
https://doi.org/10.1109/iedm19573.2019.8993555