PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture
Data acquisition for monitoring the spiky activity of large-scale SNN hardware architectures are a challenge due to their time constraints, complexity, large logic size, and so on. This paper presents a versatile PSoC-Based Data Acquisition prototype, where a specialized Master Device is used for th...
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| Інші автори: | , |
| Формат: | article |
| Мова: | eng |
| Опубліковано: |
2018
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| Онлайн доступ: | https://ieeexplore.ieee.org/document/8580286 https://hdl.handle.net/20.500.14809/3439 |
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Додати тег | _version_ | 1862854374716342272 |
|---|---|
| author | Zapata, Mireya |
| author2 | Balaji, Upasana Madrenas, Jordi |
| author2_role | author author |
| author_facet | Zapata, Mireya Balaji, Upasana Madrenas, Jordi |
| author_role | author |
| collection | Repositorio Universidad Tecnológica Indoamérica |
| dc.creator.none.fl_str_mv | Zapata, Mireya Balaji, Upasana Madrenas, Jordi |
| dc.date.none.fl_str_mv | 2018 2022-06-30T16:31:11Z 2022-06-30T16:31:11Z |
| dc.identifier.none.fl_str_mv | https://ieeexplore.ieee.org/document/8580286 https://hdl.handle.net/20.500.14809/3439 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. 17 December 2018. 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018. Cuenca. 15 October 2018 through 19 October 2018 |
| dc.rights.none.fl_str_mv | https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Universidad Tecnológica Indoamérica instname:Universidad Tecnológica Indoamérica instacron:UTI |
| dc.title.none.fl_str_mv | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Data acquisition for monitoring the spiky activity of large-scale SNN hardware architectures are a challenge due to their time constraints, complexity, large logic size, and so on. This paper presents a versatile PSoC-Based Data Acquisition prototype, where a specialized Master Device is used for this purpose. It benefits from the heterogeneous nature of SoC platforms that allows it to host programmable logic together with a hard-core ARM processor integrating memory and a variety of peripherals in a single chip. The presented design enables monitoring the performance of a multi-chip neural network through a single Ethernet interface in a hardware and software co-design, which is combined with an application developed in Python that allows the visualization on the PC of a dynamic raster plot of neural activity. In addition, an example of full platform functionality is shown. © 2018 IEEE. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | UTI_e775b78fb405d1496434ec9b59db95f1 |
| instacron_str | UTI |
| institution | UTI |
| instname_str | Universidad Tecnológica Indoamérica |
| language | eng |
| network_acronym_str | UTI |
| network_name_str | Repositorio Universidad Tecnológica Indoamérica |
| oai_identifier_str | oai:repositorio.uti.edu.ec:20.500.14809/3439 |
| publishDate | 2018 |
| publisher.none.fl_str_mv | 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. 17 December 2018. 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018. Cuenca. 15 October 2018 through 19 October 2018 |
| reponame_str | Repositorio Universidad Tecnológica Indoamérica |
| repository.mail.fl_str_mv | . |
| repository.name.fl_str_mv | Repositorio Universidad Tecnológica Indoamérica - Universidad Tecnológica Indoamérica |
| repository_id_str | 0 |
| rights_invalid_str_mv | https://creativecommons.org/licenses/by/4.0/ |
| spelling | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware ArchitectureZapata, MireyaBalaji, UpasanaMadrenas, JordiData acquisition for monitoring the spiky activity of large-scale SNN hardware architectures are a challenge due to their time constraints, complexity, large logic size, and so on. This paper presents a versatile PSoC-Based Data Acquisition prototype, where a specialized Master Device is used for this purpose. It benefits from the heterogeneous nature of SoC platforms that allows it to host programmable logic together with a hard-core ARM processor integrating memory and a variety of peripherals in a single chip. The presented design enables monitoring the performance of a multi-chip neural network through a single Ethernet interface in a hardware and software co-design, which is combined with an application developed in Python that allows the visualization on the PC of a dynamic raster plot of neural activity. In addition, an example of full platform functionality is shown. © 2018 IEEE.2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. 17 December 2018. 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018. Cuenca. 15 October 2018 through 19 October 20182022-06-30T16:31:11Z2022-06-30T16:31:11Z2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://ieeexplore.ieee.org/document/8580286https://hdl.handle.net/20.500.14809/3439enghttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessreponame:Repositorio Universidad Tecnológica Indoaméricainstname:Universidad Tecnológica Indoaméricainstacron:UTI2022-07-09T16:25:11Zoai:repositorio.uti.edu.ec:20.500.14809/3439Institucionalhttps://repositorio.uti.edu.ec/Institución privadahttps://indoamerica.edu.ec/https://repositorio.uti.edu.ec/oai.Ecuador...opendoar:02022-07-09T16:25:11Repositorio Universidad Tecnológica Indoamérica - Universidad Tecnológica Indoaméricafalse |
| spellingShingle | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture Zapata, Mireya |
| status_str | publishedVersion |
| title | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| title_full | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| title_fullStr | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| title_full_unstemmed | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| title_short | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| title_sort | PSoC-Based Real-Time Data Acquisition for a Scalable Spiking Neural Network Hardware Architecture |
| url | https://ieeexplore.ieee.org/document/8580286 https://hdl.handle.net/20.500.14809/3439 |