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Title: PaViz: A Power-Adaptive Framework for Optimal Power and Performance of Scientific Visualization Algorithms

Authors:
; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1366964
Report Number(s):
LLNL-CONF-727082
DOE Contract Number:
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Presented at: Eurographics Symposium on Parallel Graphics and Visualization, Barcelona, Spain, Jun 12 - Jun 13, 2017
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Labasan, S, Larsen, M, Rountree, B, and Childs, H. PaViz: A Power-Adaptive Framework for Optimal Power and Performance of Scientific Visualization Algorithms. United States: N. p., 2017. Web.
Labasan, S, Larsen, M, Rountree, B, & Childs, H. PaViz: A Power-Adaptive Framework for Optimal Power and Performance of Scientific Visualization Algorithms. United States.
Labasan, S, Larsen, M, Rountree, B, and Childs, H. Wed . "PaViz: A Power-Adaptive Framework for Optimal Power and Performance of Scientific Visualization Algorithms". United States. doi:. https://www.osti.gov/servlets/purl/1366964.
@article{osti_1366964,
title = {PaViz: A Power-Adaptive Framework for Optimal Power and Performance of Scientific Visualization Algorithms},
author = {Labasan, S and Larsen, M and Rountree, B and Childs, H},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}
}

Conference:
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