Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tahmoures Shabanian"'
Autor:
Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 10, Iss 4, p 33 (2020)
AI evolution is accelerating and Deep Neural Network (DNN) inference accelerators are at the forefront of ad hoc architectures that are evolving to support the immense throughput required for AI computation. However, much more energy efficient design
Externí odkaz:
https://doaj.org/article/f9b11576b3d84eef9635bf7b43e1e056
Publikováno v:
IEEE Transactions on Transportation Electrification. 8:752-766
This paper presents a magnetic field-based method for vehicle misalignment estimation in Dynamic Wireless Power Transfer (DWPT) systems. Road-embedded Transmitter (Tx) pads are employed to both charge a moving Electric Vehicle (EV) and participate in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39ccc1c72169d05eabb034c540811d7b
https://doi.org/10.1109/tte.2021.3091969
https://doi.org/10.1109/tte.2021.3091969
Autor:
Tahmoures Shabanian, Noel Daniel Gundi, Pramesh Pandey, Sanghamitra Roy, Koushik Chakraborty, Prabal Basu
Publikováno v:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 29:1790-1799
Modern deep neural network (DNN) applications demand a remarkable processing throughput usually unmet by traditional Von Neumann architectures. Consequently, hardware accelerators, comprising a sea of multiplier-and-accumulate (MAC) units, have recen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::026b3b0f825e22a5054c30a0ca495dab
https://doi.org/10.1109/tvlsi.2021.3106858
https://doi.org/10.1109/tvlsi.2021.3106858
Autor:
Koushik Chakraborty, Pramesh Pandey, Zhen Zhang, Prabal Basu, Noel Daniel Gundi, Tahmoures Shabanian, Sanghamitra Roy
Publikováno v:
ASP-DAC
Electrical and Computer Engineering Faculty Publications
Electrical and Computer Engineering Faculty Publications
Modern deep neural network (DNN) applications demand a remarkable processing throughput usually unmet by traditional Von Neumann architectures. Consequently, hardware accelerators, comprising a sea of multiplier and accumulate (MAC) units, have recen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef4c74a5089a79339db7c8eb8a57c42d
https://doi.org/10.1109/asp-dac47756.2020.9045479
https://doi.org/10.1109/asp-dac47756.2020.9045479
Autor:
Koushik Chakraborty, Prabal Basu, Noel Daniel Gundi, Mitchell Craig Patrick, Sanghamitra Roy, Tahmoures Shabanian, Pramesh Pandey
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 10, Iss 33, p 33 (2020)
Electrical and Computer Engineering Faculty Publications
Journal of Low Power Electronics and Applications
Volume 10
Issue 4
Electrical and Computer Engineering Faculty Publications
Journal of Low Power Electronics and Applications
Volume 10
Issue 4
AI evolution is accelerating and Deep Neural Network (DNN) inference accelerators are at the forefront of ad hoc architectures that are evolving to support the immense throughput required for AI computation. However, much more energy efficient design
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ee32f34ae7d79b96770a914595ce45c
https://doi.org/10.3390/jlpea10040033
https://doi.org/10.3390/jlpea10040033
Publikováno v:
ISLPED
The proliferation of multicore devices with a strict thermal budget has aided to the research in Near-Threshold Computing (NTC). However, the operation of a Graphics Processing Unit (GPU) at the NTC region has still remained recondite. In this work,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bab13ecb94fdd4d06ae91f022af3a3f6
https://doi.org/10.1145/3218603.3218644
https://doi.org/10.1145/3218603.3218644