Exploring scaling efficiency of intel loihi neuromorphic processor
dc.contributor.author | Uludağ, Recep Buğra | |
dc.contributor.author | Çaǧdaş, S. | |
dc.contributor.author | Işler, Y. S. | |
dc.contributor.author | Şengör, N. S. | |
dc.contributor.author | Aktürk, İsmail | |
dc.date.accessioned | 2024-02-27T08:43:28Z | |
dc.date.available | 2024-02-27T08:43:28Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 979-835032649-9 | |
dc.identifier.uri | http://hdl.handle.net/10679/9233 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/10382884 | |
dc.description.abstract | In this paper, we focus on examining how scaling efficiency evolves in winner-take-all (WTA) network models on Intel Loihi neuromorphic processor, as network-related features such as network size, neuron type, and connectivity scheme change. By analyzing these relationships, our study aims to shed light on the intricate interplay between SNN features and the efficiency of neuromorphic systems as they scale up. The findings presented in this paper are expected to enhance the comprehension of scaling efficiency in neuromorphic hardware, providing valuable insights for researchers and developers in optimizing the performance of large-scale SNNs on neuromorphic architectures. | en_US |
dc.description.sponsorship | Intel’s Neuromorphic Research Community | |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | 2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS) | |
dc.rights | restrictedAccess | |
dc.title | Exploring scaling efficiency of intel loihi neuromorphic processor | en_US |
dc.type | Conference paper | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0003-1970-2507 & YÖK ID 349836) Aktürk, İsmail | |
dc.contributor.ozuauthor | Aktürk, İsmail | |
dc.identifier.doi | 10.1109/ICECS58634.2023.10382884 | en_US |
dc.subject.keywords | Intel loihi | en_US |
dc.subject.keywords | Scaling efficiency | en_US |
dc.subject.keywords | Spiking neural networks | en_US |
dc.subject.keywords | Winner-take-all | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85183587411 | |
dc.contributor.ozugradstudent | Uludağ, Recep Buğra | |
dc.relation.publicationcategory | Conference Paper - International - Institutional Academic Staff and Graduate Student |
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