137 citations · 253 across the 12 of their papers we have counts for
5 papers · 1 filter
A Bespoke Design Approach to Low-Power Printed Microprocessors for Machine Learning Applications
Panagiotis Chaidos, Giorgos Armeniakos, Sotirios Xydis +1
Printed electronics have gained significant traction in recent years, presenting a viable path to integrating computing into everyday items, from disposable products to low-cost he…
Mixed-precision Neural Networks on RISC-V Cores: ISA extensions for Multi-Pumped Soft SIMD Operations
Giorgos Armeniakos, Alexis Maras, Sotirios Xydis +1
Recent advancements in quantization and mixed-precision approaches offers substantial opportunities to improve the speed and energy efficiency of Neural Networks (NN). Research has…
Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications
Vasileios Leon, Muhammad Abdullah Hanif, Giorgos Armeniakos +4
The challenging deployment of compute-intensive applications from domains such as Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computin…
Approximate Computing Survey, Part I: Terminology and Software & Hardware Approximation Techniques
Vasileios Leon, Muhammad Abdullah Hanif, Giorgos Armeniakos +4
The rapid growth of demanding applications in domains applying multimedia processing and machine learning has marked a new era for edge and cloud computing. These applications invo…
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…