Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Dingwen Tao"'
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 34:923-937
Autor:
Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, Franck Cappello
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 33:4440-4457
Autor:
Pu Jiao, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello
Publikováno v:
Proceedings of the VLDB Endowment. 16:697-710
Today's scientific simulations and instruments are producing a large amount of data, leading to difficulties in storing, transmitting, and analyzing these data. While error-controlled lossy compressors are effective in significantly reducing data vol
Autor:
Lipeng Wan, David Pugmire, Xin Liang, Matthew Wolf, Dingwen Tao, Jieyang Chen, James Kress, Scott Klasky, Qing Liu, Norbert Podhorszki, Ben Whitney
Publikováno v:
IEEE Transactions on Computers. 71:1522-1536
Data management is becoming increasingly important in dealing with the large amounts of data produced by large-scale scientific simulations and instruments. Existing multilevel compression algorithms offer a promising way to manage scientific data at
Publikováno v:
IEEE Systems Journal, 16(3), 3770-3781
IEEE Systems Journal 16 (2022) 3
IEEE Systems Journal 16 (2022) 3
In the past decade, we have witnessed a dramatically increasing volume of data collected from varied sources. The explosion of data has transformed the world as more information is available for collection and analysis than ever before. To maximize t
Autor:
Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
Publikováno v:
Proceedings of the VLDB Endowment. 15:886-899
Training wide and deep neural networks (DNNs) require large amounts of storage resources such as memory because the intermediate activation data must be saved in the memory during forward propagation and then restored for backward propagation. Howeve
Publikováno v:
2022 30th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS).
Autor:
Xinyu Chen, Marco Minutoli, Jiannan Tian, Mahantesh Halappanavar, Ananth Kalyanaraman, Dingwen Tao
Publikováno v:
Web of Science
Influence maximization aims to select k most-influential vertices or seeds in a network, where influence is defined by a given diffusion process. Although computing optimal seed set is NP-Hard, efficient approximation algorithms exist. However, even
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b8ac418d25c5982d656ac8f5f6daa3b
http://arxiv.org/abs/2208.00613
http://arxiv.org/abs/2208.00613
Autor:
Dingwen Tao, Sheng Di
This slide is to introduce the NSF CSSI project - HyLoC, which aims to develop a hybrid lossy compression framework to automatically construct the best-fit compression for diverse user objectives in data-intensive scientific research.
NSF CDS&E
NSF CDS&E
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8334c0c1678dff4d57fa59571dcd2fcd
This poster is to present the progress of an NSF-funded project, called ROCCI, at 2022 NSF CSSI PI Meeting. The ROCCI project aims to develop a Requirement-Oriented Compression Cyber-Infrastructure (ROCCI) for data-intensive domains such as astrophys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52ca27eff54bf7ab6916ff12922b7b6f