A High Throughput Generative Vector Autoregression Model for Stochastic Synapses
Abstract
By imitating the synaptic connectivity and plasticity of the brain, emerging electronic nanodevices offer new opportunities as the building blocks of neuromorphic systems. One challenge for largescale simulations of computational architectures based on emerging devices is to accurately capture device response, hysteresis, noise, and the covariance structure in the temporal domain as well as between the different device parameters. We address this challenge with a high throughput generative model for synaptic arrays that is based on a recently available type of electrical measurement data for resistive memory cells. We map this real world data onto a vector autoregressive stochastic process to accurately reproduce the device parameters and their cross-correlation structure. While closely matching the measured data, our model is still very fast; we provide parallelized implementations for both CPUs and GPUs and demonstrate array sizes above one billion cells and throughputs exceeding one hundred million weight updates per second, above the pixel rate of a 30 frames/s 4K video stream.
Authors 7
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Affiliation as printed
IWE II , RWTH Aachen University , Aachen , Germany
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Western Digital (United States)
Affiliation as printed
Western Digital San Jose Research Center , CA , USA
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Commissariat à l'Énergie Atomique et aux Énergies Alternatives · CEA Grenoble · Laboratoire d'Électronique des Technologies de l'Information
Affiliation as printed
CEA , LETI , MINATEC Campus , Grenoble , France
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Commissariat à l'Énergie Atomique et aux Énergies Alternatives · CEA Grenoble · Laboratoire d'Électronique des Technologies de l'Information
Affiliation as printed
CEA , LETI , MINATEC Campus , Grenoble , France
Now with Weebit Nano Ltd
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Affiliation as printed
IWE II , RWTH Aachen University , Aachen , Germany
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Affiliation as printed
IWE II , RWTH Aachen University , Aachen , Germany
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Western Digital (United States)
Affiliation as printed
Western Digital San Jose Research Center , CA , USA
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