129 citations · 334 across the 11 of their papers we have counts for
4 papers · 1 filter
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution
Filip Badan, Lukas Sekanina
Automated design methods for convolutional neural networks (CNNs) have recently been developed in order to increase the design productivity. We propose a neuroevolution method capa…
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining
Vojtech Mrazek, Zdenek Vasicek, Lukas Sekanina +2
The state-of-the-art approaches employ approximate computing to reduce the energy consumption of DNN hardware. Approximate DNNs then require extensive retraining afterwards to reco…
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components
Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasicek +2
Approximate computing is an emerging paradigm for developing highly energy-efficient computing systems such as various accelerators. In the literature, many libraries of elementary…
Automated Circuit Approximation Method Driven by Data Distribution
Zdenek Vasicek, Vojtech Mrazek, Lukas Sekanina
We propose an application-tailored data-driven fully automated method for functional approximation of combinational circuits. We demonstrate how an application-level error metric s…