137 citations · 253 across the 12 of their papers we have counts for
12 papers
Hybrid unary-binary design for multiplier-less printed Machine Learning classifiers
Giorgos Armeniakos, Theodoros Mantzakidis, Dimitrios Soudris
Printed Electronics (PE) provide a flexible, cost-efficient alternative to silicon for implementing machine learning (ML) circuits, but their large feature sizes limit classifier c…
MaRVIn: A Cross-Layer Mixed-Precision RISC-V Framework for DNN Inference, from ISA Extension to Hardware Acceleration
Giorgos Armeniakos, Alexis Maras, Sotirios Xydis +1
The evolution of quantization and mixed-precision techniques has unlocked new possibilities for enhancing the speed and energy efficiency of NNs. Several recent studies indicate th…
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…
Accelerating TinyML Inference on Microcontrollers through Approximate Kernels
Giorgos Armeniakos, Georgios Mentzos, Dimitrios Soudris
The rapid growth of microcontroller-based IoT devices has opened up numerous applications, from smart manufacturing to personalized healthcare. Despite the widespread adoption of e…
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…
On-sensor Printed Machine Learning Classification via Bespoke ADC and Decision Tree Co-Design
Giorgos Armeniakos, Paula L. Duarte, Priyanjana Pal +3
Printed electronics (PE) technology provides cost-effective hardware with unmet customization, due to their low non-recurring engineering and fabrication costs. PE exhibit features…