Litcius/Paper detail

Unconventional Computing With Memristive Nanocircuits

Evangelos Tsipas, Theodoros Panagiotis Chatzinikolaou, Κάρολος-Αλέξανδρος Τσάκαλος, Konstantinos Rallis, Rafailia-Eleni Karamani, Iosif-Angelos Fyrigos, Stavros Kitsios, Panagiotis Bousoulas, Dimitrios Tsoukalas, Georgios Ch. Sirakoulis

2022IEEE Nanotechnology Magazine13 citationsDOIOpen Access PDF

Abstract

Computing demands are growing rapidly as bigdata and artificial intelligence applications become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be quite promising for the development of novel circuits and systems. These systems can contribute to the resolution of a wider variety of problems while also providing improvements to existing techniques. As the von Neumann architecture’s expected performance, which has been dominant for the past several decades, is now hindered by physical limitations, novel computing architectures, assisted by novel materials and circuit devices, are starting to emerge and provide promising results. The topic of this work is to examine the memory and computing capabilities of emergent memristor-based nanocircuits and demonstrate their advantages compared to their classical counterparts.

Topics & Concepts

MemristorVon Neumann architectureComputer scienceUnconventional computingVariety (cybernetics)Quantum computerComputer architectureIn-Memory ProcessingArtificial intelligenceData scienceComputer engineeringDistributed computingQuantumElectrical engineeringEngineeringPhysicsWeb search querySearch engineInformation retrievalQuery by ExampleQuantum mechanicsOperating systemAdvanced Memory and Neural ComputingPhotoreceptor and optogenetics researchNeuroscience and Neural Engineering