Zobrazeno 1 - 10
of 138
pro vyhledávání: '"Philip E Davis"'
Autor:
Philip E. Davis
The Scalping of the Great Sioux Nation recalls Davis'early upbringing and education on two Indian reservations. Davis also assesses the policies of the United States government regarding the status of Indians in society. Scalping is not too strong a
Publikováno v:
Future Generation Computer Systems. 142:75-89
Autor:
Shuangxi Zhang, Berk Geveci, Matthew Wolf, Kevin Huck, E. Suchyta, Cameron W. Smith, Ruonan Wang, Stephane Ethier, Philip E. Davis, Manish Parashar, Pradeep Subedi, Gabriele Merlo, Abolaji Adesoji, Norbert Podhorszki, Qing Liu, Todd Munson, Shirley Moore, Mark S. Shephard, C.S. Chang, Jeremy Logan, Jong Choi, Lipeng Wan, Kai Germaschewski, David Pugmire, Ian Foster, Scott Klasky, Kshitij Mehta, Chris Harris, Julien Dominski
Publikováno v:
The International Journal of High Performance Computing Applications. 36:106-128
We present the Exascale Framework for High Fidelity coupled Simulations (EFFIS), a workflow and code coupling framework developed as part of the Whole Device Modeling Application (WDMApp) in the Exascale Computing Project. EFFIS consists of a library
Publikováno v:
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid).
Publikováno v:
SSRN Electronic Journal.
Autor:
Philip E. Davis, Shaohua Duan, Keita Teranishi, Pradeep Subedi, Manish Parashar, Hemanth Kolla, Marc Gamell
Publikováno v:
ACM Transactions on Parallel Computing. 7:1-29
The dramatic increase in the scale of current and planned high-end HPC systems is leading new challenges, such as the growing costs of data movement and IO, and the reduced mean time between failures (MTBF) of system components. In-situ workflows, i.
Publikováno v:
2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC).
Publikováno v:
2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS).
Publikováno v:
CLUSTER
While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing