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A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End Inference of Real-World Deep Neural Networks

Jan 04, 2022
Angelo Garofalo, Gianmarco Ottavi, Francesco Conti, Geethan Karunaratne, Irem Boybat, Luca Benini, Davide Rossi

* 14 pages (not including final biography page), 13 figures (excluded authors pictures) 

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AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator

Nov 10, 2021
Chuteng Zhou, Fernando Garcia Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough

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ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning

Mar 25, 2020
Vinay Joshi, Geethan Karunaratne, Manuel Le Gallo, Irem Boybat, Christophe Piveteau, Abu Sebastian, Bipin Rajendran, Evangelos Eleftheriou

* 5 pages. 5 figures. Accepted at ISCAS 2020 for publication 

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Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

May 28, 2019
S. R. Nandakumar, Irem Boybat, Manuel Le Gallo, Evangelos Eleftheriou, Abu Sebastian, Bipin Rajendran

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Fatiguing STDP: Learning from Spike-Timing Codes in the Presence of Rate Codes

Jun 17, 2017
Timoleon Moraitis, Abu Sebastian, Irem Boybat, Manuel Le Gallo, Tomas Tuma, Evangelos Eleftheriou

* 8 pages, 8 figures, presented at IJCNN in May 2017 

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