Zobrazeno 1 - 10
of 210
pro vyhledávání: '"Diederik Verkest"'
Autor:
Pouya Houshmand, Giuseppe M. Sarda, Vikram Jain, Kodai Ueyoshi, Ioannis A. Papistas, Man Shi, Qilin Zheng, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst
Publikováno v:
IEEE Journal of Solid-State Circuits. 58:203-215
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7d00c76e8400f5204cf2f3909442412
https://doi.org/10.1109/jssc.2022.3214064
https://doi.org/10.1109/jssc.2022.3214064
Autor:
S. S. Teja Nibhanupudi, Divya Prasad, Shidhartha Das, Odysseas Zografos, Alex Robinson, Anshul Gupta, Alessio Spessot, Peter Debacker, Diederik Verkest, Julien Ryckaert, Geert Hellings, James Myers, Brian Cline, Jaydeep P. Kulkarni
Publikováno v:
IEEE Transactions on Electron Devices. 69:4453-4459
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ce4f049a68c97db20fe30a94e14c916
https://doi.org/10.1109/ted.2022.3186657
https://doi.org/10.1109/ted.2022.3186657
Autor:
Nathan Laubeuf, Jonas Doevenspeck, Ioannis A. Papistas, Michele Caselli, Stefan Cosemans, Peter Vrancx, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Francky Catthoor, Rudy Lauwereins
Publikováno v:
ACM Transactions on Design Automation of Electronic Systems. 27:1-21
Analog in Memory Computing (AiMC) based neural network acceleration is a promising solution to increase the energy efficiency of deep neural networks deployment. However, the quantization requirements of these analog systems are not compatible with s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a50bed920fdc64780ebd87cc1a37351
https://doi.org/10.1145/3498328
https://doi.org/10.1145/3498328
Autor:
Simei Yang, Debjyoti Bhattacharjee, Vinay B. Y. Kumar, Saikat Chatterjee, Sayandip De, Peter Debacker, Diederik Verkest, Arindam Mallik, Francky Catthoor
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 12:508-521
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56858cbb7aecf42bfd471873a482ef14
https://doi.org/10.1109/jetcas.2022.3171826
https://doi.org/10.1109/jetcas.2022.3171826
Publikováno v:
2022 IEEE International Symposium on Circuits and Systems (ISCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d11fa8e7250d7870073af330a1b2fc1
https://doi.org/10.1109/iscas48785.2022.9937613
https://doi.org/10.1109/iscas48785.2022.9937613
Publikováno v:
2022 IEEE International Symposium on Circuits and Systems (ISCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2fbb0d8c52de25c9cdc6c578591975b
https://doi.org/10.1109/iscas48785.2022.9937962
https://doi.org/10.1109/iscas48785.2022.9937962
Autor:
M. H. Na, Attilio Belmonte, J. Doevenspeck, Nouredine Rassoul, Romain Delhougne, Arindam Mallik, D. Saito, Ioannis A. Papistas, Gouri Sankar Kar, Stefan Cosemans, M. Perumkunnil, Peter Debacker, H. Oh, Diederik Verkest
Publikováno v:
IEEE Transactions on Electron Devices. 67:4616-4620
We propose, for the first time, an indium gallium zinc oxide (IGZO)-based 2T1C compute cell (IGZO-cell) for analog in-memory computing. To assess the impact of an IGZO-cell-based array including the periphery on power and accuracy, a PyTorch framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bdd3ace0c527f208a22365edce5cd77
https://doi.org/10.1109/ted.2020.3025986
https://doi.org/10.1109/ted.2020.3025986
Autor:
Peter Debacker, J. Doevenspeck, Robin Degraeve, Andrea Fantini, Wim Dehaene, Diederik Verkest, Rudy Lauwereins
Publikováno v:
IEEE Transactions on Electron Devices. 67:505-511
The joint device-algorithm development of a resistive RAM (RRAM)-based sequence learning system is presented. The low-voltage gradual RESET of oxygen-vacancy-based RRAM was characterized and modeled by kinetic Monte Carlo simulations based on the hou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71aa41163097226ed7aa32cb1d72b804
https://doi.org/10.1109/ted.2019.2957067
https://doi.org/10.1109/ted.2019.2957067
Autor:
Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe M. Sarda, Vikram Jain, Man Shi, Qilin Zheng, Sebastian Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst
Publikováno v:
2022 IEEE International Solid- State Circuits Conference (ISSCC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::417d5f08444dac120175b0648ce982d3
https://doi.org/10.1109/isscc42614.2022.9731716
https://doi.org/10.1109/isscc42614.2022.9731716
Autor:
J. Doevenspeck, Peter Debacker, Peter Vrancx, Wim Dehaene, Arindam Mallik, Diederik Verkest, Rudy Lauwereins, Nathan Laubeuf
Publikováno v:
IJCNN
Analog in memory computing (AiMC) is a promising hardware solution to efficiently perform inference with deep neural networks (DNNs). Similar to digital DNN accelerators, AiMC systems benefit from aggressively quantized DNNs. In addition, AiMC system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61ce201c504a3a3f0c1aacfccdad8887
https://doi.org/10.1109/ijcnn52387.2021.9533684
https://doi.org/10.1109/ijcnn52387.2021.9533684