Pioneering energy-efficient AI with innovative ferroelectric technology

As AI becomes increasingly integrated into sectors such as healthcare, autonomous vehicles and smart cities, conventional computing architectures face notable limitations in processing speed and energy efficiency. The 'ViTFOX' project brings together eight partners from Europe and Korea to develop a ground-breaking Vision Transformer architecture based on ferroelectric oxide, allowing considerable reductions in energy consumption and latency. Unlike traditional architectures, which often rely on separate memory and processing units, ViTFOX aims to incorporate computing directly into memory, attaining an exceptional energy efficiency of over 50TOPS/W. The European Union is funding the project with €1.5 million.

Traditional computing architectures face considerable limitations in processing speed and energy efficiency when handling the vast amounts of data generated in today's digital landscape. Neuromorphic systems, systems that mimic the working method of the human brain, using specialised hardware, such as ferroelectric devices, to execute computations more efficiently and effectively, allowing real-time processing and decision-making. This approach not only improves the performance of AI applications, such as image recognition and natural language processing, but also decreases energy consumption, making it a sustainable solution for future technology.

The ViTFOX project is at the forefront of advancing AI by developing energy-efficient neuromorphic computing systems. At the heart of the ViTFOX project is the Vision Transformer (ViT) architecture, which is designed to perform complex AI computations while consuming less energy. Vision Transformers are a type of neural network architecture that excels in image recognition tasks by processing visual data more effectively than traditional methods. The project aims to create a ViT that utilises ferroelectric oxide materials to achieve exceptional energy efficiency of over 50 TOPS/W, which is crucial for AI-powered edge applications. "We aim to push the boundaries of current technology by developing hardware-software co-optimisation platforms, novel materials, and integration methods that will not only enhance AI performance but also ensure sustainability in energy consumption, "says Professor Dr Thomas Kämpfe, project leader at Fraunhofer IPMS, one of the partners in the consortium. "We want to significantly contribute to the semiconductor industry, addressing both the technical challenges of emerging memory technologies and the societal need for efficient computing solutions," he adds.

Collaboration between Europe and Korea to advance the state-of-the-art technology

In total, the ViTFOX consortium comprises eight partners from leading research institutions, universities, and technology development laboratories in Europe and Korea. The project aims to strengthen the leading position of EU and Korea in Hafnia-based Silicon-compatible ferroelectric electronics, a field which was pioneered in Europe and has attracted significant interest from Korean researchers. The project will advance technology beyond the state of the art in the entire value chain, from materials and devices to heterogeneous and monolithic integration, and design and simulation of the ViT circuits and systems. The project is particularly significant as it capitalises on the recent advancements in ferroelectric materials, specifically hafnium-zirconium oxide (HZO), which has shown to be compatible with conventional silicon components and is an outstanding promise in improving memory devices and reducing power consumption.

Three of the project objectives target the design and fabrication of the main components of the ViT, namely a Compute-in-Memory demonstrator, a circuit level simulator and a hardware-software co-optimisation platform with ferroelectric oxides. The platform will support two types of emerging memories, high-density 3D FeRAM developed in Korea and epitaxial ferroelectric tunnel junctions developed in Europe. This strong collaboration enables the partners to employ their collective expertise in materials science, semiconductor technology, and AI, pushing the boundaries of this emerging field.