Zobrazeno 1 - 10
of 2 258
pro vyhledávání: '"Graham, John P."'
Autor:
Altintas, Ilkay, Perez, Ismael, Mishin, Dmitry, Trouillaud, Adrien, Irving, Christopher, Graham, John, Tatineni, Mahidhar, DeFanti, Thomas, Strande, Shawn, Smarr, Larry, Norman, Michael L.
Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specialized capabilities at the system-, science- and service-level in addition
Externí odkaz:
http://arxiv.org/abs/2211.06918
Autor:
Würthwein, Frank, Guiang, Jonathan, Arora, Aashay, Davila, Diego, Graham, John, Mishin, Dima, Hutton, Thomas, Sfiligoi, Igor, Newman, Harvey, Balcas, Justas, Lehman, Tom, Yang, Xi, Guok, Chin
Unique scientific instruments designed and operated by large global collaborations are expected to produce Exabyte-scale data volumes per year by 2030. These collaborations depend on globally distributed storage and compute to turn raw data into scie
Externí odkaz:
http://arxiv.org/abs/2209.13714
Autor:
Lehman, Tom, Yang, Xi, Guok, Chin, Wuerthwein, Frank, Sfiligoi, Igor, Graham, John, Arora, Aashay, Mishin, Dima, Davila, Diego, Guiang, Jonathan, Hutton, Tom, Newman, Harvey, Balcas, Justas
This paper describes a vision and work in progress to elevate network resources and data transfer management to the same level as compute and storage in the context of services access, scheduling, life cycle management, and orchestration. While domai
Externí odkaz:
http://arxiv.org/abs/2203.08280
Publikováno v:
2021 IEEE 17th International Conference on eScience (eScience), 2021, pp. 239-240
HTCondor is a major workload management system used in distributed high throughput computing (dHTC) environments, e.g., the Open Science Grid. One of the distinguishing features of HTCondor is the native support for data movement, allowing it to oper
Externí odkaz:
http://arxiv.org/abs/2107.03947
Publikováno v:
EPJ Web of Conferences 245, 07059 (2020)
Commercial Cloud computing is becoming mainstream, with funding agencies moving beyond prototyping and starting to fund production campaigns, too. An important aspect of any scientific computing production campaign is data movement, both incoming and
Externí odkaz:
http://arxiv.org/abs/2002.04568
Akademický článek
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Autor:
Xueying Ai, Ali Mahmoud El-Badri, Maria Batool, Hongxiang Lou, Gengdong Gao, Chenyang Bai, Zongkai Wang, Chunji Jiang, Xinhua Zhao, Bo Wang, Jie Kuai, Zhenghua Xu, Jing Wang, Graham John King, Haiqiu Yu, Guangsheng Zhou, Tingdong Fu
Publikováno v:
International Journal of Molecular Sciences, Vol 25, Iss 6, p 3308 (2024)
The global expansion of rapeseed seed quality has been focused on maintaining glucosinolate (GSL) and erucic acid (EA) contents. However, the influence of seed GSL and EA contents on the germination process under drought stress remains poorly underst
Externí odkaz:
https://doaj.org/article/61ba23220948493dbefe4466a22e5c4a
Autor:
Kangas, Tuomas, Fruchter, Andrew S., Cenko, S. Bradley, Corsi, Alessandra, Postigo, Antonio de Ugarte, Pe'er, Asaf, Vogel, Stuart N., Cucchiara, Antonino, Gompertz, Benjamin, Graham, John, Levan, Andrew, Misra, Kuntal, Perley, Daniel A., Racusin, Judith, Tanvir, Nial
We present post-jet-break \textit{HST}, VLA and \textit{Chandra} observations of the afterglow of the long $\gamma$-ray bursts GRB 160625B (between 69 and 209 days) and GRB 160509A (between 35 and 80 days). We calculate the post-jet-break decline rat
Externí odkaz:
http://arxiv.org/abs/1906.03493
Autor:
Graham, John F.
In support of ongoing projects we have compiled a database of supernovae with host metallicities determined from spectroscopy in the Sloan Digital Sky Survey (SDSS) which we are providing as a catalog for the general use of the community. Here we pro
Externí odkaz:
http://arxiv.org/abs/1905.13197
Autor:
Altintas, Ilkay, Marcus, Kyle, Nealey, Isaac, Sellars, Scott L., Graham, John, Mishin, Dima, Polizzi, Joel, Crawl, Daniel, DeFanti, Thomas, Smarr, Larry
The advances in data, computing and networking over the last two decades led to a shift in many application domains that includes machine learning on big data as a part of the scientific process, requiring new capabilities for integrated and distribu
Externí odkaz:
http://arxiv.org/abs/1903.06802