Zobrazeno 1 - 10
of 374
pro vyhledávání: '"UYAR, AHMET"'
Autor:
Perera, Niranda, Kamburugamuve, Supun, Widanage, Chathura, Abeykoon, Vibhatha, Uyar, Ahmet, Shan, Kaiying, Maithree, Hasara, Lenadora, Damitha, Kanewala, Thejaka Amila, Fox, Geoffrey
The data science community today has embraced the concept of Dataframes as the de facto standard for data representation and manipulation. Ease of use, massive operator coverage, and popularization of R and Python languages have heavily influenced th
Externí odkaz:
http://arxiv.org/abs/2209.06146
Autor:
UYAR, Ahmet1 ahmetuyar@aku.edu.tr
Publikováno v:
International Journal of Economic & Administrative Studies. 2024, Issue 44, p169-187. 19p.
This report describes 1) how we use Intel's Optane DCPMM in the memory Mode. We investigate the the scalability of applications on a single Optane machine, using Subgraph counting as memory-intensive graph problem. We test with various input graph an
Externí odkaz:
http://arxiv.org/abs/2109.11021
Autor:
Abeykoon, Vibhatha, Kamburugamuve, Supun, Widanage, Chathura, Perera, Niranda, Uyar, Ahmet, Kanewala, Thejaka Amila, von Laszewski, Gregor, Fox, Geoffrey
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machine learning. These applications are built around efficient data abstrac
Externí odkaz:
http://arxiv.org/abs/2108.06001
Autor:
Kamburugamuve, Supun, Widanage, Chathura, Perera, Niranda, Abeykoon, Vibhatha, Uyar, Ahmet, Kanewala, Thejaka Amila, von Laszewski, Gregor, Fox, Geoffrey
Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas developed in various data science and data engineering frameworks. Th
Externí odkaz:
http://arxiv.org/abs/2107.12807
Autor:
Perera, Niranda, Abeykoon, Vibhatha, Widanage, Chathura, Kamburugamuve, Supun, Kanewala, Thejaka Amila, Wickramasinghe, Pulasthi, Uyar, Ahmet, Maithree, Hasara, Lenadora, Damitha, Fox, Geoffrey
In the current era of Big Data, data engineering has transformed into an essential field of study across many branches of science. Advancements in Artificial Intelligence (AI) have broadened the scope of data engineering and opened up new application
Externí odkaz:
http://arxiv.org/abs/2010.14596
Autor:
Abeykoon, Vibhatha, Perera, Niranda, Widanage, Chathura, Kamburugamuve, Supun, Kanewala, Thejaka Amila, Maithree, Hasara, Wickramasinghe, Pulasthi, Uyar, Ahmet, Fox, Geoffrey
Data engineering is becoming an increasingly important part of scientific discoveries with the adoption of deep learning and machine learning. Data engineering deals with a variety of data formats, storage, data extraction, transformation, and data m
Externí odkaz:
http://arxiv.org/abs/2010.06312
Autor:
Widanage, Chathura, Perera, Niranda, Abeykoon, Vibhatha, Kamburugamuve, Supun, Kanewala, Thejaka Amila, Maithree, Hasara, Wickramasinghe, Pulasthi, Uyar, Ahmet, Gunduz, Gurhan, Fox, Geoffrey
The amazing advances being made in the fields of machine and deep learning are a highlight of the Big Data era for both enterprise and research communities. Modern applications require resources beyond a single node's ability to provide. However this
Externí odkaz:
http://arxiv.org/abs/2007.09589
Autor:
Uyar, Ahmet, Cellat, Mustafa, Kanat, Özgür, Etyemez, Muhammed, Kutlu, Tuncer, Deveci, Mehmet Yılmaz Zeki, Yavaş, İlker, Kuzu, Müslüm
Publikováno v:
In Reproductive Toxicology October 2023 121
Autor:
UYAR, Ahmet1 ahmetuyar@aku.edu.tr, UYAR, Kübra2 kkilicaslan@aku.edu.tr
Publikováno v:
Uludag Bee Journal. 2024, Vol. 24 Issue 1, p126-141. 16p.