Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Parallel and distributed processing"'
Autor:
Tiancheng Zhang, Hanyu Mao, Hengyu Liu, Yingjie Liu, Minghe Yu, Wenhui Wu, Ge Yu, Baoze Wei, Yajuan Guan
Publikováno v:
Mathematics, Vol 11, Iss 24, p 5002 (2023)
Knowledge proficiency refers to the extent to which students master knowledge and reflects their cognitive status. To accurately assess knowledge proficiency, various pedagogical theories have emerged. Bloom’s cognitive theory, proposed in 1956 as
Externí odkaz:
https://doaj.org/article/7a092726fa634b11ab04a4919c2ac2f0
Publikováno v:
Journal of Cloud Computing: Advances, Systems and Applications, Vol 9, Iss 1, Pp 1-20 (2020)
Abstract Task stragglers in MapReduce jobs dramatically impede job execution of data-intensive computing in cloud data centers. This impedance is due to the uneven distribution of input data, heterogeneous data nodes, resource contention situations,
Externí odkaz:
https://doaj.org/article/a6cf25d76dff4fa3840f03a7d34b21a9
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-23 (2019)
Abstract Deep Learning is an increasingly important subdomain of artificial intelligence, which benefits from training on Big Data. The size and complexity of the model combined with the size of the training dataset makes the training process very co
Externí odkaz:
https://doaj.org/article/e0f68ce3a7914c8b8832fe995e7ab6ac
Autor:
Zhou, Xuan
Publikováno v:
法政大学大学院紀要. 情報科学研究科編. 18:1-6
This paper proposes an updated method to determine the reference point for acceleration based on Multi-Objective Evolutionary Optimization Algorithm Parallel and Distributed Decomposition (MOEA/D) to process a multi-core environment. A method had bee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::2533cbca3ae1243bb7b7a1d867de425e
http://hdl.handle.net/10114/00026286
http://hdl.handle.net/10114/00026286
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Journal of Big Data, Vol 4, Iss 1, Pp 1-17 (2017)
Abstract With the increasing demand for examining and extracting patterns from massive amounts of data, it is critical to be able to train large models to fulfill the needs that recent advances in the machine learning area create. L-BFGS (Limited-mem
Externí odkaz:
https://doaj.org/article/78d94785026c4e50bebacd70e3cf90bf
Conference
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Chang, Hung-Ching
The demands of exascale computing systems and applications have pushed for a rapid, continual design paradigm coupled with increasing design complexities from the interaction between the application, the middleware, and the underlying system hardware
Externí odkaz:
http://hdl.handle.net/10919/51682
Publikováno v:
Proceedings of the IEEE
Proceedings of the IEEE, Institute of Electrical and Electronics Engineers, 2021, 109 (8), pp.1282-1305. ⟨10.1109/JPROC.2021.3087029⟩
Proceedings of the IEEE, 2021, 109 (8), pp.1282-1305. ⟨10.1109/JPROC.2021.3087029⟩
Proceedings of the IEEE, Institute of Electrical and Electronics Engineers, 2021, 109 (8), pp.1282-1305. ⟨10.1109/JPROC.2021.3087029⟩
Proceedings of the IEEE, 2021, 109 (8), pp.1282-1305. ⟨10.1109/JPROC.2021.3087029⟩
International audience; This article gives a survey of state-of-the-art methods for processing remotely sensed big data and thoroughly investigates existing parallel implementations on diverse popular high-performance computing platforms. The pros/co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a33c027355d6446cc9ed50385575519
https://hal.archives-ouvertes.fr/hal-03429692
https://hal.archives-ouvertes.fr/hal-03429692