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pro vyhledávání: '"Simon, William Andrew"'
HyperDimensional Computing (HDC) as a machine learning paradigm is highly interesting for applications involving continuous, semi-supervised learning for long-term monitoring. However, its accuracy is not yet on par with other Machine Learning (ML) a
Externí odkaz:
http://arxiv.org/abs/2206.04746
Akademický článek
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Akademický článek
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Autor:
Qureshi, Yasir Mahmood, Simon, William Andrew, Zapater, Marina, Olcoz, Katzalin, Atienza, David
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 18(4):1-27
Autor:
Simon, William Andrew, Galicia, Juan-Martin, Levisse, Alexandre Sébastien Julien, Zapater Sancho, Marina, Atienza Alonso, David
In-Memory Computing (IMC) solutions, and particularly bitline computing in SRAM, appear promising as they mitigate one of the most energy consuming aspects in computation: data movement. In this work we propose a fast (2.4Ghz for bitwise operations a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::f9b91e8f6fbb009ba31b13f219deff18
https://infoscience.epfl.ch/record/265152
https://infoscience.epfl.ch/record/265152
Autor:
Simon, William Andrew, Qureshi, Yasir Mahmood, Levisse, Alexandre Sébastien Julien, Zapater Sancho, Marina, Atienza Alonso, David
The increasing ubiquity of edge devices in the consumer market, along with their ever more computationally expensive workloads, necessitate corresponding increases in computing power to support such workloads. In-memory computing is attractive in edg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::90d007e95937033d7987d3e3232c742e
https://infoscience.epfl.ch/record/264782
https://infoscience.epfl.ch/record/264782
Autor:
Simon, William Andrew, Rios, Marco Antonio, Levisse, Alexandre Sébastien, Zapater, Marina, Atienza Alonso, David
A random access memory having a memory array having a plurality of local memory groups, each local memory group including a plurality of bitcells arranged in a bitcell column, a pair of local bitlines operatively connected to the plurality of bitcell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::363d8d1be51b0e194fbe40c3a3175158
https://infoscience.epfl.ch/record/288196
https://infoscience.epfl.ch/record/288196
Autor:
Levisse, Alexandre Sébastien Julien, Rios, Marco Antonio, Simon, William Andrew, Gaillardon, Pierre-Emmanuel Julien Marc, Atienza Alonso, David
With the surge in complexity of edge workloads, it appeared in the scientific community that such workloads cannot be anymore overflown to the cloud due to the huge edge device to server communication energy cost and the high energy consumption induc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::4ec2f226b23528389930ffffc42fd65c
https://infoscience.epfl.ch/record/272717
https://infoscience.epfl.ch/record/272717
Autor:
Simon, William Andrew
Utilization of edge devices has exploded in the last decade, with such use cases as wearable devices, autonomous driving, and smart homes. As their ubiquity grows, so do expectations of their capabilities. Simultaneously, their formfactor and use cas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1368129006ff76be44aa6846861da19
https://infoscience.epfl.ch/record/296065
https://infoscience.epfl.ch/record/296065
Autor:
Simon, William Andrew, Qureshi, Yasir Mahmood, Levisse, Alexandre, Zapater, Marina, Atienza, David
Publikováno v:
Proceedings of the 2019 on Great Lakes Symposium on VLSI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=sygma_______::811b5902c520d256a818a1e472d3b068