Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Aleksandr Drozd"'
Publikováno v:
Data Science and Engineering, Vol 4, Iss 2, Pp 157-175 (2019)
Abstract Word embedding has been well accepted as an important feature in the area of natural language processing (NLP). Specifically, the Word2Vec model learns high-quality word embeddings and is widely used in various NLP tasks. The training of Wor
Externí odkaz:
https://doaj.org/article/c4daf56761204571adb845a16bd33f18
Publikováno v:
Artificial Intelligence for Science ISBN: 9789811265662
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d33c793917cf689aa4c00cdc80e0702
https://doi.org/10.1142/9789811265679_0009
https://doi.org/10.1142/9789811265679_0009
Autor:
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Andrew A. Chien, Raymond Bair, Jeffrey S. Vetter, John Shalf
Publikováno v:
Computing in Science & Engineering. 24:85-90
Publikováno v:
The International Journal of High Performance Computing Applications. :109434202311666
In this thought-provoking article, we discuss certain myths and legends that are folklore among members of the high-performance computing community. We gathered these myths from conversations at conferences and meetings, product advertisements, paper
Autor:
Thao Truong Nguyen, François Trahay, Jens Domke, Aleksandr Drozd, Emil Vatai, Jianwei Liao, Mohamed Wahib, Balazs Gerofi
Publikováno v:
HAL
Autor:
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonca, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
Scientific communities are increasingly adopting machine learning and deep learning models in their applications to accelerate scientific insights. High performance computing systems are pushing the frontiers of performance with a rich diversity of h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1d0a43c2f3602f2bf9c531d477eabaf
http://arxiv.org/abs/2110.11466
http://arxiv.org/abs/2110.11466
Publikováno v:
Data Science and Engineering, Vol 4, Iss 2, Pp 157-175 (2019)
Word embedding has been well accepted as an important feature in the area of natural language processing (NLP). Specifically, the Word2Vec model learns high-quality word embeddings and is widely used in various NLP tasks. The training of Word2Vec is
Autor:
Jens Domke, Satoshi Matsuoka, Yosuke Oyama, Artur Podobas, Shweta Salaria, Mohamed WahibT, Peng ChenT, Daichi Mukunoki, Lingqi Zhang, Aleksandr Drozd, Emil Vatai
Publikováno v:
IPDPS
Matrix engines or units, in different forms and affinities, are becoming a reality in modern processors; CPUs and otherwise. The current and dominant algorithmic approach to Deep Learning merits the commercial investments in these units, and deduced
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71008949f6299f44b6303e2d2939f164
http://arxiv.org/abs/2010.14373
http://arxiv.org/abs/2010.14373
Autor:
Aleksandr Drozd, Jens Domke, Truong Thao Nguyen, Lingqi Zhang, Ryousei Takano, Haoyu Zhang, Mohamed Wahib, Satoshi Matsuoka
Publikováno v:
SC
The dedicated memory of hardware accelerators can be insufficient to store all weights and/or intermediate states of large deep learning models. Although model parallelism is a viable approach to reduce the memory pressure issue, significant modifica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e75e30fc72e6ee4623572db16d2a197c
http://arxiv.org/abs/2008.11421
http://arxiv.org/abs/2008.11421
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030206550
ISC
ISC
The graphic processing units (GPUs) have become a primary source of heterogeneity in today’s computing systems. With the rapid increase in number and types of GPUs available, finding the best hardware accelerator for each application is a challenge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1ac787811c4c88036b3a4cf698f043a
https://doi.org/10.1007/978-3-030-20656-7_3
https://doi.org/10.1007/978-3-030-20656-7_3