Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing
Abstract The development of devices that can modulate their conductance under the application of electrical stimuli constitutes a fundamental step towards the realization of synaptic connectivity in neural networks. Optimization of synaptic functionality requires the understanding of the analogue co...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2018-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-018-25376-x |
| _version_ | 1818857705658384384 |
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| author | Jacopo Frascaroli Stefano Brivio Erika Covi Sabina Spiga |
| author_facet | Jacopo Frascaroli Stefano Brivio Erika Covi Sabina Spiga |
| author_sort | Jacopo Frascaroli |
| collection | DOAJ |
| description | Abstract The development of devices that can modulate their conductance under the application of electrical stimuli constitutes a fundamental step towards the realization of synaptic connectivity in neural networks. Optimization of synaptic functionality requires the understanding of the analogue conductance update under different programming conditions. Moreover, properties of physical devices such as bounded conductance values and state-dependent modulation should be considered as they affect storage capacity and performance of the network. This work provides a study of the conductance dynamics produced by identical pulses as a function of the programming parameters in an HfO2 memristive device. The application of a phenomenological model that considers a soft approach to the conductance boundaries allows the identification of different operation regimes and to quantify conductance modulation in the analogue region. Device non-linear switching kinetics is recognized as the physical origin of the transition between different dynamics and motivates the crucial trade-off between degree of analog modulation and memory window. Different kinetics for the processes of conductance increase and decrease account for device programming asymmetry. The identification of programming trade-off together with an evaluation of device variations provide a guideline for the optimization of the analogue programming in view of hardware implementation of neural networks. |
| first_indexed | 2024-12-19T08:44:39Z |
| format | Article |
| id | doaj.art-1d5d6f4413e04217b7a43cd6966c0cba |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-19T08:44:39Z |
| publishDate | 2018-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-1d5d6f4413e04217b7a43cd6966c0cba2022-12-21T20:28:49ZengNature PortfolioScientific Reports2045-23222018-05-018111210.1038/s41598-018-25376-xEvidence of soft bound behaviour in analogue memristive devices for neuromorphic computingJacopo Frascaroli0Stefano Brivio1Erika Covi2Sabina Spiga3Laboratorio MDM, IMM-CNRLaboratorio MDM, IMM-CNRLaboratorio MDM, IMM-CNRLaboratorio MDM, IMM-CNRAbstract The development of devices that can modulate their conductance under the application of electrical stimuli constitutes a fundamental step towards the realization of synaptic connectivity in neural networks. Optimization of synaptic functionality requires the understanding of the analogue conductance update under different programming conditions. Moreover, properties of physical devices such as bounded conductance values and state-dependent modulation should be considered as they affect storage capacity and performance of the network. This work provides a study of the conductance dynamics produced by identical pulses as a function of the programming parameters in an HfO2 memristive device. The application of a phenomenological model that considers a soft approach to the conductance boundaries allows the identification of different operation regimes and to quantify conductance modulation in the analogue region. Device non-linear switching kinetics is recognized as the physical origin of the transition between different dynamics and motivates the crucial trade-off between degree of analog modulation and memory window. Different kinetics for the processes of conductance increase and decrease account for device programming asymmetry. The identification of programming trade-off together with an evaluation of device variations provide a guideline for the optimization of the analogue programming in view of hardware implementation of neural networks.https://doi.org/10.1038/s41598-018-25376-x |
| spellingShingle | Jacopo Frascaroli Stefano Brivio Erika Covi Sabina Spiga Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing Scientific Reports |
| title | Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| title_full | Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| title_fullStr | Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| title_full_unstemmed | Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| title_short | Evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| title_sort | evidence of soft bound behaviour in analogue memristive devices for neuromorphic computing |
| url | https://doi.org/10.1038/s41598-018-25376-x |
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