5 papers
An RRAM-based Hardware Implementation of a Radial Basis Function Neuron for Edge Classifiers
Georgios Papandroulidakis, Shady Agwa, Themis Prodromakis
The deployment of modern machine learning (ML) solutions on resource-constrained edge devices highlights implementation challenges. This is especially true for extreme edge applica…
OISMA: On-the-fly In-memory Stochastic Multiplication Architecture for Matrix-Multiplication Workloads
Shady Agwa, Yihan Pan, Georgios Papandroulidakis +1
Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication workloads representing the major computa…
A Hybrid Edge Classifier: Combining TinyML-Optimised CNN with RRAM-CMOS ACAM for Energy-Efficient Inference
Kieran Woodward, Eiman Kanjo, Georgios Papandroulidakis +2
In recent years, the development of smart edge computing systems to process information locally is on the rise. Many near-sensor machine learning (ML) approaches have been implemen…
A 9T4R RRAM-Based ACAM for Analogue Template Matching at the Edge
Georgios Papandroulidakis, Shady Agwa, Ahmet Cirakoglu +1
The continuous shift of computational bottlenecks to the memory access and data transfer, especially for AI applications, poses the urgent needs of re-engineering the computer arch…
An RRAM-Based Implementation of a Template Matching Circuit for Low-Power Analogue Classification
Patrick Foster, Georgios Papandroulidakis, Alex Serb +1
Recent advances in machine learning and neuro-inspired systems enabled the increased interest in efficient pattern recognition at the edge. A wide variety of applications, such as…