ASC Directions in Machine Learning @LANL
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
To find ways to impact ASC work in the IC, V&V and PEM. In particular in-line ML as opposed to post processing. We have more mature work in the CSSE/FOUS area of ASC
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1422916
- Report Number(s):
- LA-UR-18-21068
- Country of Publication:
- United States
- Language:
- English
Similar Records
Report of experiments and evidence for ASC L2 milestone 4467 : demonstration of a legacy application's path to exascale.
(U) Ristra Next Generation Code Report
NNSA ASC Exascale Environment Planning, Applications Working Group, Report February 2011
Technical Report
·
Thu Mar 01 00:00:00 EST 2012
·
OSTI ID:1422916
+21 more
(U) Ristra Next Generation Code Report
Technical Report
·
Fri Sep 22 00:00:00 EDT 2017
·
OSTI ID:1422916
NNSA ASC Exascale Environment Planning, Applications Working Group, Report February 2011
Technical Report
·
Fri Feb 25 00:00:00 EST 2011
·
OSTI ID:1422916
+6 more