Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Ian Karlin"'
Autor:
Dong H. Ahn, Xiaohua Zhang, Jeffrey Mast, Stephen Herbein, Francesco Di Natale, Dan Kirshner, Sam Ade Jacobs, Ian Karlin, Daniel J. Milroy, Bronis De Supinski, Brian Van Essen, Jonathan Allen, Felice C. Lightstone
Composite science workflows are gaining traction to manage the combined effects of (1) extreme hardware heterogeneity in new High Performance Computing (HPC) systems and (2) growing software complexity – effects necessitated by the convergence of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::712a2f2d0e1bf900d0871a4c86014a52
Autor:
Kevin McLoughlin, Felice C. Lightstone, David Hysom, Sam Ade Jacobs, Dong H. Ahn, Tim Moon, Ian Karlin, John Gyllenhaal, Jonathan E. Allen, Derek Jones, Pythagoras Watson, Brian Van Essen
Publikováno v:
The International Journal of High Performance Computing Applications. 35:469-482
We improved the quality and reduced the time to produce machine learned models for use in small molecule antiviral design. Our globally asynchronous multi-level parallel training approach strong scales to all of Sierra with up to 97.7% efficiency. We
Autor:
Brian Ryujin, Arturo Vargas, Ian Karlin, Shawn Dawson, Kenneth Weiss, Adam Bertsch, M. McKinley, Michael Collette, Si Hammond, Kevin Pedretti, Robert Rieben
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ef6cd644b8c790d10415b060d01fe2
https://doi.org/10.2172/1838264
https://doi.org/10.2172/1838264
Publikováno v:
The International Symposium on Memory Systems.
Autor:
Noel Chalmers, Jean-Sylvain Camier, Tzanio V. Kolev, Yohann Dudouit, Kasia Swirydowicz, Lukas Spies, Thilina Rathnayake, Tim Warburton, Valeria Barra, Misun Min, Veselin Dobrev, Ahmad Abdelfattah, Ian Karlin, Jeremy Thompson, Jack Dongarra, Mark S. Shephard, Stanimire Tomov, Vladimir Tomov, Will Pazner, Ananias G. Tomboulides, Jed Brown, Paul Fischer, Ali Karakus, Natalie Beams, Elia Merzari, Stefan Kerkemeier, David Medina, Yu-Hsiang Lan, Cameron W. Smith, Aleksandr Obabko
Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::850982f4dd8a5bb5c1c40c219a4e7392
http://arxiv.org/abs/2109.04996
http://arxiv.org/abs/2109.04996
Autor:
Barry Rountree, Adam Bertsch, Dong H. Ahn, Nathan A. Besaw, Brian Van Essen, Bronis R. de Supinski, Tapasya Patki, Ian Karlin
Publikováno v:
CLUSTER
Scalable management of user workloads on large-scale supercomputers remains a challenge due to the tradeoff between capturing adequate detail for analysis from various data sources and minimizing overhead. Co-designed frameworks, such as IBM’s Clus
Cognitive simulation (CogSim) is an important and emerging workflow for HPC scientific exploration and scientific machine learning (SciML). One challenging workload for CogSim is the replacement of one component in a complex physical simulation with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7eedbc3408ce8bf05ffa75b9e11a0ad