53 citations · 127 across the 9 of their papers we have counts for
9 papers
Evolutionary Approximation of Ternary Neurons for On-sensor Printed Neural Networks
Vojtech Mrazek, Argyris Kokkinis, Panagiotis Papanikolaou +5
Printed electronics offer ultra-low manufacturing costs and the potential for on-demand fabrication of flexible hardware. However, significant intrinsic constraints stemming from t…
Variability-Aware Approximate Circuit Synthesis via Genetic Optimization
Konstantinos Balaskas, Florian Klemme, Georgios Zervakis +3
One of the major barriers that CMOS devices face at nanometer scale is increasing parameter variation due to manufacturing imperfections. Process variations severely inhibit the re…
Energy-Aware Heterogeneous Federated Learning via Approximate DNN Accelerators
Kilian Pfeiffer, Konstantinos Balaskas, Kostas Siozios +1
In Federated Learning (FL), devices that participate in the training usually have heterogeneous resources, i.e., energy availability. In current deployments of FL, devices that do…
Hardware-Aware DNN Compression via Diverse Pruning and Mixed-Precision Quantization
Konstantinos Balaskas, Andreas Karatzas, Christos Sad +4
Deep Neural Networks (DNNs) have shown significant advantages in a wide variety of domains. However, DNNs are becoming computationally intensive and energy hungry at an exponential…
Bespoke Approximation of Multiplication-Accumulation and Activation Targeting Printed Multilayer Perceptrons
Florentia Afentaki, Gurol Saglam, Argyris Kokkinis +3
Printed Electronics (PE) feature distinct and remarkable characteristics that make them a prominent technology for achieving true ubiquitous computing. This is particularly relevan…
Hardware-Aware Automated Neural Minimization for Printed Multilayer Perceptrons
Argyris Kokkinis, Georgios Zervakis, Kostas Siozios +2
The demand of many application domains for flexibility, stretchability, and porosity cannot be typically met by the silicon VLSI technologies. Printed Electronics (PE) has been int…
Approximate Decision Trees For Machine Learning Classification on Tiny Printed Circuits
Konstantinos Balaskas, Georgios Zervakis, Kostas Siozios +2
Although Printed Electronics (PE) cannot compete with silicon-based systems in conventional evaluation metrics, e.g., integration density, area and performance, PE offers attractiv…
Automated Design Approximation to Overcome Circuit Aging
Konstantinos Balaskas, Georgios Zervakis, Hussam Amrouch +2
Transistor aging phenomena manifest themselves as degradations in the main electrical characteristics of transistors. Over time, they result in a significant increase of cell propa…
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch
Dimitrios Danopoulos, Georgios Zervakis, Kostas Siozios +2
Current state-of-the-art employs approximate multipliers to address the highly increased power demands of DNN accelerators. However, evaluating the accuracy of approximate DNNs is…