137 citations · 511 across the 22 of their papers we have counts for
9 papers · 1 filter
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…
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 Computing and the Efficient Machine Learning Expedition
Jörg Henkel, Hai Li, Anand Raghunathan +4
Approximate computing (AxC) has been long accepted as a design alternative for efficient system implementation at the cost of relaxed accuracy requirements. Despite the AxC researc…
Hardware Approximate Techniques for Deep Neural Network Accelerators: A Survey
Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris +1
Deep Neural Networks (DNNs) are very popular because of their high performance in various cognitive tasks in Machine Learning (ML). Recent advancements in DNNs have brought beyond…
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…
CoMeT: An Integrated Interval Thermal Simulation Toolchain for 2D, 2.5D, and 3D Processor-Memory Systems
Lokesh Siddhu, Rajesh Kedia, Shailja Pandey +4
Processing cores and the accompanying main memory working in tandem enable the modern processors. Dissipating heat produced from computation, memory access remains a significant pr…
Positive/Negative Approximate Multipliers for DNN Accelerators
Ourania Spantidi, Georgios Zervakis, Iraklis Anagnostopoulos +2
Recent Deep Neural Networks (DNNs) managed to deliver superhuman accuracy levels on many AI tasks. Several applications rely more and more on DNNs to deliver sophisticated services…
Reliability-Aware Quantization for Anti-Aging NPUs
Sami Salamin, Georgios Zervakis, Ourania Spantidi +3
Transistor aging is one of the major concerns that challenges designers in advanced technologies. It profoundly degrades the reliability of circuits during its lifetime as it slows…
Hardware Trojan Detection Using Controlled Circuit Aging
Virinchi Roy Surabhi, Prashanth Krishnamurthy, Hussam Amrouch +4
This paper reports a novel approach that uses transistor aging in an integrated circuit (IC) to detect hardware Trojans. When a transistor is aged, it results in delays along sever…