Synaptogen: A Cross-Domain Generative Device Model for Large-Scale Neuromorphic Circuit Design Article Swipe
Tyler Hennen
,
Leon Brackmann
,
Tobias Ziegler
,
Sebastian Siegel
,
Stephan Menzel
,
Rainer Waser
,
Dirk J. Wouters
,
Daniel Bedau
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/ted.2024.3427616
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/ted.2024.3427616
We present a fast generative modeling approach for resistive memories that reproduces the complex statistical properties of real-world devices. By training on extensive measurement data of an integrated 1T1R array (6000 cycles of 512 devices), an autoregressive stochastic process accurately accounts for the cross-correlations between device switching parameters, while nonlinear transformations ensure agreement with the joint cycle-to-cycle (C2C) and device-to-device (D2D) write distributions. In addition to a high-level programming version, the model is also implemented in Verilog-A to enable efficient simulation of analog circuits. This statistically comprehensive model can be used to simulate crossbar sizes with up to 1024 1024 devices, and benchmarks show that it achieves read/write speeds several orders of magnitude higher than a variability-aware physics-based compact model and over 10 faster than even a simplified and deterministic compact model.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/ted.2024.3427616
- OA Status
- hybrid
- Cited By
- 3
- References
- 31
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4400811526Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/ted.2024.3427616Digital Object Identifier
- Title
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Synaptogen: A Cross-Domain Generative Device Model for Large-Scale Neuromorphic Circuit DesignWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-19Full publication date if available
- Authors
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Tyler Hennen, Leon Brackmann, Tobias Ziegler, Sebastian Siegel, Stephan Menzel, Rainer Waser, Dirk J. Wouters, Daniel BedauList of authors in order
- Landing page
-
https://doi.org/10.1109/ted.2024.3427616Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1109/ted.2024.3427616Direct OA link when available
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Neuromorphic engineering, Computer science, Generative model, Algorithm, Electronic engineering, Engineering, Artificial intelligence, Artificial neural network, Generative grammarTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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31Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2584335437, https://openalex.org/W3082899001, https://openalex.org/W4385411987, https://openalex.org/W3039320313, https://openalex.org/W2329040051, https://openalex.org/W2420237597, https://openalex.org/W2807268759, https://openalex.org/W4388349073, https://openalex.org/W2245173025, https://openalex.org/W2587492433, https://openalex.org/W4280629371, https://openalex.org/W2583536366, https://openalex.org/W4241115065, https://openalex.org/W2008901850, https://openalex.org/W3199467182, https://openalex.org/W2914119805, https://openalex.org/W3106278248, https://openalex.org/W1501896809, https://openalex.org/W4385896568, https://openalex.org/W4292121737, https://openalex.org/W4323022446, https://openalex.org/W3017900531, https://openalex.org/W3112740243, https://openalex.org/W3176606713, https://openalex.org/W3141540147, https://openalex.org/W3033519076, https://openalex.org/W4288437883, https://openalex.org/W4328049695, https://openalex.org/W2058171930, https://openalex.org/W1521233350, https://openalex.org/W3007317489 |
| referenced_works_count | 31 |
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