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Title: Adaptive Mesh Refinement in the Fastlane

Abstract

Adaptive Mesh Refinement (AMR) allows us to dramatically reduce memory usage by dynamically distributing resources to areas of physical significance.

Authors:
 [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1467356
Report Number(s):
LA-UR-18-28159
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; AMR; Phantom Cell; GPU

Citation Formats

Dunning, Daniel Jeffrey, and Marts, William Pepper. Adaptive Mesh Refinement in the Fastlane. United States: N. p., 2018. Web. doi:10.2172/1467356.
Dunning, Daniel Jeffrey, & Marts, William Pepper. Adaptive Mesh Refinement in the Fastlane. United States. doi:10.2172/1467356.
Dunning, Daniel Jeffrey, and Marts, William Pepper. Mon . "Adaptive Mesh Refinement in the Fastlane". United States. doi:10.2172/1467356. https://www.osti.gov/servlets/purl/1467356.
@article{osti_1467356,
title = {Adaptive Mesh Refinement in the Fastlane},
author = {Dunning, Daniel Jeffrey and Marts, William Pepper},
abstractNote = {Adaptive Mesh Refinement (AMR) allows us to dramatically reduce memory usage by dynamically distributing resources to areas of physical significance.},
doi = {10.2172/1467356},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {8}
}

Technical Report:

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