Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Manya Ghobadi"'
Autor:
Alexander Sludds, Saumil Bandyopadhyay, Zaijun Chen, Zhizhen Zhong, Jared Cochrane, Liane Bernstein, Darius Bunandar, P. Ben Dixon, Scott A. Hamilton, Matthew Streshinsky, Ari Novack, Tom Baehr-Jones, Michael Hochberg, Manya Ghobadi, Ryan Hamerly, Dirk Englund
Publikováno v:
Science. 378:270-276
Advances in deep neural networks (DNNs) are transforming science and technology. However, the increasing computational demands of the most powerful DNNs limit deployment on low-power devices, such as smartphones and sensors – and this trend is acce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0df8438dffca626eeadef5957b7eba89
https://doi.org/10.1126/science.abq8271
https://doi.org/10.1126/science.abq8271
Publikováno v:
Proceedings of the 21st ACM Workshop on Hot Topics in Networks.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0bdf1c9d133bcc0f94243f690e109f3
https://doi.org/10.1145/3563766.3564115
https://doi.org/10.1145/3563766.3564115
Autor:
Mingran Yang, Alex Baban, Valery Kugel, Jeff Libby, Scott Mackie, Swamy Sadashivaiah Renu Kananda, Chang-Hong Wu, Manya Ghobadi
Publikováno v:
Proceedings of the ACM SIGCOMM 2022 Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f3227e6dbf93faa0da2d2476b6e6932
https://doi.org/10.1145/3544216.3544262
https://doi.org/10.1145/3544216.3544262
Publikováno v:
Proceedings of the ACM SIGCOMM 2022 Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15223df6ab638704f6f3ecb19cdfdddb
https://doi.org/10.1145/3544216.3544252
https://doi.org/10.1145/3544216.3544252
Autor:
Alexander Sludds, Ryan Hamerly, Saumil Bandyopadhyay, Zaijun Chen, Zhizhen Zhong, Liane Bernstein, Manya Ghobadi, Dirk Englund
Publikováno v:
2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce1d651c5bece07a42ed5f982c3ee231
https://doi.org/10.23919/oecc/psc53152.2022.9850215
https://doi.org/10.23919/oecc/psc53152.2022.9850215
Publikováno v:
MIT web domain
SIGMETRICS (Abstracts)
SIGMETRICS (Abstracts)
This paper presents a systematic approach to identify and quantify the types of structures featured by packettraces in communication networks. Our approach leverages an information-theoretic methodology, based oniterative randomization and compressio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91aa72c2e89fb2c04bcf4b92c4b7ca4d
https://doi.org/10.1145/3379486
https://doi.org/10.1145/3379486
Autor:
Alexander Sludds, Ryan Hamerly, Saumil Bandyopadhyay, Zhizhen Zhong, Zaijun Chen, Liane Bernstein, Manya Ghobadi, Dirk Englund
Publikováno v:
Optical Fiber Communication Conference (OFC) 2022.
We present experimental demonstrations of ultra-low power edge computing enabled by wavelength division multiplexed optical links and time-integrating optical receivers. Initial experimentation demonstrations show ≲ 10 fJ of optical energy per MAC.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dabac4010f32804dd70459512896dd6a
https://doi.org/10.1364/ofc.2022.th3a.3
https://doi.org/10.1364/ofc.2022.th3a.3
Autor:
Manya Ghobadi
Publikováno v:
Optical Fiber Communication Conference (OFC) 2022.
The ever-growing demand for accurate machine learning models resulted in an increase in dataset and model sizes of deep neural networks. This paper discusses reconfigurable optical networks as the key enabler for scaling AI systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea0dec0a3c4690fc2aea21e49ca08e84
https://doi.org/10.1364/ofc.2022.th1g.1
https://doi.org/10.1364/ofc.2022.th1g.1
Publikováno v:
ACM SIGMETRICS Performance Evaluation Review. 50:99-100
The bandwidth and latency requirements of modern datacenter applications have led researchers to propose various topology designs using static, dynamic demand-oblivious (rotor), and/or dynamic demand-aware switches. However, given the diverse nature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9819a2732765d704cfb2a05f33a92ae5
https://doi.org/10.1145/3547353.3522635
https://doi.org/10.1145/3547353.3522635
Autor:
Alexander Sludds, Ryan Hamerly, Weiyang Wang, Dirk Englund, Zhizhen Zhong, Liane Bernstein, Manya Ghobadi
Publikováno v:
OptSys@SIGCOMM
We present In-network Optical Inference (IOI), a system providing low-latency machine learning inference by leveraging programmable switches and optical matrix multiplication. IOI consists of a novel transceiver module designed specifically to perfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2becc013d42f2ff0d4d1721f0b2aceb6
https://doi.org/10.1145/3473938.3474508
https://doi.org/10.1145/3473938.3474508