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Highlight | Spintronics
Convolutional neural networks are adapted to perform cognitive tasks such as image and video recognition, or language processing. In order to implement these networks more efficiently, researchers at IRIG have integrated spintronic devices in an architecture combining a Binary Ensemble Convolutional Neural Network. Specific tools allowed to evaluate this disruptive combination that is less complex and consumes less power.
Convolutional neural networks (CNN) are efficient for certain tasks such as image or text recognition. However, the classical design of a computer in which the processor and the memory are physically separated is not compatible with a neural network. Indeed, the calculations requiring that the synapses exchange frequently between the neurons the information stored in the memory (we speak of synaptic weight) that causes a considerable slowdown. Researchers at IRIG have therefore used spintronic devices that allow a parallel implementation of the networks in which the calculation and storage are integrated in the same block.
Researchers have developed electronic memories called memristors whose resistance changes continuously as a function of applied current. In a memory architecture called "crossbar", the memristors code the synaptic weight as an electrical resistance, in order to perform calculations with analog currents that will be converted into digital values. The goal is to realize a convolutional neural network based on memristors, which keeps the same performances while minimizing the complexity and without additional hardware cost. However, as the manufacturing process of these spintronic devices is recent, the accuracy of the computation still needs to be made reliable. Moreover, the synaptic weights can only take two binary states which makes it difficult to access different resistance levels in order to mimic a synapse.
Tchendjou GT, Danouchi K, Prenat G, and Anghel A.
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.