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David Briand
2020 – today
- 2023
- [j2]Ivan Miro-Panades, Benoît Tain
, Jean-Frédéric Christmann
, David Coriat, Romain Lemaire
, Clement Jany
, Baudouin Martineau
, Fabrice Chaix, Guillaume Waltener
, Emmanuel Pluchart
, Jean-Philippe Noel, Adam Makosiej, Maxime Montoya
, Simone Bacles-Min, David Briand, Jean-Marc Philippe, Yvain Thonnart
, Alexandre Valentian, Frédéric Heitzmann, Fabien Clermidy:
SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration. IEEE J. Solid State Circuits 58(6): 1782-1797 (2023) - [i1]Ivan Miro-Panades, Benoît Tain, Jean-Frédéric Christmann, David Coriat, Romain Lemaire, Clement Jany, Baudouin Martineau, Fabrice Chaix, Guillaume Waltener, Emmanuel Pluchart, Jean-Philippe Noel, Adam Makosiej, Maxime Montoya, Simone Bacles-Min, David Briand, Jean-Marc Philippe, Yvain Thonnart, Alexandre Valentian, Frédéric Heitzmann, Fabien Clermidy:
SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration. CoRR abs/2304.13726 (2023) - 2022
- [c6]Thibault Allenet, David Briand, Olivier Bichler, Olivier Sentieys:
Disentangled Loss for Low-Bit Quantization-Aware Training. CVPR Workshops 2022: 2787-2791 - [c5]José Flich
, Laura Medina, Izan Catalán
, Carles Hernández, Andrea Bragagnolo
, Fabrice Auzanneau, David Briand:
Efficient Inference Of Image-Based Neural Network Models In Reconfigurable Systems With Pruning And Quantization. ICIP 2022: 2491-2495 - 2021
- [c4]Olivier Sentieys, Silviu-Ioan Filip, David Briand, David Novo, Etienne Dupuis, Ian O'Connor, Alberto Bosio:
AdequateDL: Approximating Deep Learning Accelerators. DDECS 2021: 37-40 - 2020
- [c3]Ivan Miro Panades, Benoît Tain
, Jean-Frédéric Christmann, David Coriat, Romain Lemaire, Clement Jany
, Baudouin Martineau, Fabrice Chaix, Anthony Quelen, Emmanuel Pluchart, Jean-Philippe Noel, Reda Boumchedda, Adam Makosiej, Maxime Montoya
, Simone Bacles-Min, David Briand, Jean-Marc Philippe, Alexandre Valentian, Frédéric Heitzmann, Edith Beigné, Fabien Clermidy:
SamurAI: A 1.7MOPS-36GOPS Adaptive Versatile IoT Node with 15, 000× Peak-to-Idle Power Reduction, 207ns Wake-Up Time and 1.3TOPS/W ML Efficiency. VLSI Circuits 2020: 1-2
2010 – 2019
- 2018
- [j1]Lilia Zaourar
, Massinissa Ait Aba, David Briand, Jean-Marc Philippe:
Task management on fully heterogeneous micro-server system: Modeling and resolution strategies. Concurr. Comput. Pract. Exp. 30(23) (2018) - [c2]Alexandre Carbon, Jean-Marc Philippe, Olivier Bichler, Renaud Schmit, Benoît Tain
, David Briand, Nicolas Ventroux, Michel Paindavoine, Olivier Brousse:
PNeuro: A scalable energy-efficient programmable hardware accelerator for neural networks. DATE 2018: 1039-1044 - 2017
- [c1]Lilia Zaourar, Massinissa Ait Aba, David Briand, Jean-Marc Philippe:
Modeling of Applications and Hardware to Explore Task Mapping and Scheduling Strategies on a Heterogeneous Micro-Server System. IPDPS Workshops 2017: 65-76
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last updated on 2024-04-25 05:43 CEST by the dblp team
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