1. Oxide based resistive memories for low power embedded applications and neuromorphic systems
- Author
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Barbara De Salvo, Daniele Garbin, Luca Perniola, E. Vianello, Natalija Jovanovic, Olivier Bichler, Olivier Thomas, Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Département d'Architectures, Conception et Logiciels Embarqués-LIST (DACLE-LIST), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), and Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA))
- Subjects
Computation theory ,Computer science ,Embedded systems ,Convolutional neural network ,02 engineering and technology ,010402 general chemistry ,Non-volatile flip-flops ,01 natural sciences ,law.invention ,Internet of Things (IOT) ,Big data ,[SPI]Engineering Sciences [physics] ,law ,Pattern recognition ,Electronic engineering ,Networks (circuits) ,Wearable technology ,Flip-flop ,business.industry ,Neuromorphic systems ,Electrical engineering ,Visual pattern recognition ,Pattern recognition systems ,021001 nanoscience & nanotechnology ,Data handling ,0104 chemical sciences ,Resistive random-access memory ,Flip flop circuits ,Neuromorphic engineering ,CMOS ,Neuromorphic circuits ,Logic gate ,Embedded application ,State (computer science) ,High-resistance state ,0210 nano-technology ,business ,Neural networks ,Hardware_LOGICDESIGN ,Logic circuits - Abstract
Conference of Symposium on Nonvolatile Memories 4 - 228th ECS Meeting ; Conference Date: 11 October 2015 Through 15 October 2015; Conference Code:115963; International audience; Oxide based resistive memories (OxRAMs) is one of the potential candidates for non-volatile logic circuits and neuromorphic circuits in the applications of wearable devices, internet of things (IoT), cloud computing, and big-data processing. One of the main OxRAMs issue is the noise behavior of the high resistance state (HRS). In this work, we will demonstrate a hybrid (CMOS logic plus ReRAM devices) Non Volatile Flip Flop designed to face OxRAM variability. Concerning neuromorphic circuits, we will focus on the impact of resistance variability on the performance of Convolutional Neural Network (CNN) systems for visual pattern recognition applications.
- Published
- 2015