20 citations · 82 across the 14 of their papers we have counts for
4 papers · 1 filter
MemSE: Fast MSE Prediction for Noisy Memristor-Based DNN Accelerators
Jonathan Kern, Sébastien Henwood, Gonçalo Mordido +4
Memristors enable the computation of matrix-vector multiplications (MVM) in memory and, therefore, show great potential in highly increasing the energy efficiency of deep neural ne…
Rethinking Pareto Frontier for Performance Evaluation of Deep Neural Networks
Vahid Partovi Nia, Alireza Ghaffari, Mahdi Zolnouri +1
Performance optimization of deep learning models is conducted either manually or through automatic architecture search, or a combination of both. On the other hand, their performan…
CNN2Gate: Toward Designing a General Framework for Implementation of Convolutional Neural Networks on FPGA
Alireza Ghaffari, Yvon Savaria
Convolutional Neural Networks (CNNs) have a major impact on our society because of the numerous services they provide. On the other hand, they require considerable computing power.…
Layerwise Noise Maximisation to Train Low-Energy Deep Neural Networks
Sébastien Henwood, François Leduc-Primeau, Yvon Savaria
Deep neural networks (DNNs) depend on the storage of a large number of parameters, which consumes an important portion of the energy used during inference. This paper considers the…