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- W4283260051 abstract "The world of electronics is urgently looking for post-CMOS solutions due to the end of Moore’s law saturating our present computing capacities. Such a post-CMOS paradigm would have to incorporate novel features at all levels from materials and devices to architectures and algorithms. The most promising candidate among several paradigms in research is classical neuromorphic computing, which mimics biological brains to solve classification and optimization problems in general. Here we will talk about how thermal properties of novel materials, such as phase change materials (e.g., Mott insulators such as VO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> and NbO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> ), offer unique functional behaviors at the device level, which we call thermally engineered memory elements (‘thermems’). Specifically, we show how thermems can be designed to express dynamics of higher-order complexity (e.g., chaos). Such complex behavior, originating from a single thermem, would require hundreds of transistor circuits to simulate. We will further show how such higher-order dynamics mimic biological behaviors such as neuron-like periodic burst spiking and chaos. Finally, we will show with examples as to how such unique higher-order dynamics can enable unique algorithmic functions that offer improved efficiencies previously not possible in digital CMOS computers." @default.
- W4283260051 created "2022-06-23" @default.
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- W4283260051 date "2022-03-06" @default.
- W4283260051 modified "2023-09-27" @default.
- W4283260051 title "Novel thermal material properties for post-CMOS neuromorphic computing" @default.
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- W4283260051 doi "https://doi.org/10.1109/edtm53872.2022.9797918" @default.
- W4283260051 hasPublicationYear "2022" @default.
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