Paper Info
Title
Making A Case For Green High-Performance Visualization Via Embedded Graphics Processors
Abstract
This paper makes a case for using low-power embedded GPUs for the purpose of executing high-performance scientific visualization tasks. We compare the greenness (i.e., power, energy, and energy-delay product -> EDP) of an embedded GPU with a CPU for commonly encountered visualization tasks using two real-world applications: (1) Modeling for Prediction Across Scale Ocean (MPAS-O) and (2) Particular Ensembles (PE). Our preliminary results show that the low-power embedded GPU is capable of handling complex visualization tasks while consuming less than 50% of the energy consumed by a CPU server. In addition, we find that the embedded GPU outperforms the CPU with dynamic voltage-frequency scaling (DVFS) enabled in a majority of the cases.
Year
DOI
Venue
2018
10.1109/IPDPSW.2018.00116
2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018)
Field
DocType
ISSN
Graphics,Central processing unit,Data visualization,Pipeline transport,Task analysis,Computer science,Visualization,Parallel computing,Scientific visualization,Scaling
Conference
2164-7062
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Vignesh Adhinarayanan1244.68
Bishwajit Dutta270.96
Wu-chun Feng32812232.50