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Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems
January 2012 (vol. 18 no. 1)
pp. 17-29
ASCII Text
x 
 
Mark Howison, E. Wes Bethel, Hank Childs, "Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 1, pp. 17-29, January, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2011.24,
author = {Mark Howison and E. Wes Bethel and Hank Childs},
title = {Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {18},
number = {1},
issn = {1077-2626},
year = {2012},
pages = {17-29},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.24},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems
IS - 1
SN - 1077-2626
SP17
EP29
EPD - 17-29
A1 - Mark Howison,
A1 - E. Wes Bethel,
A1 - Hank Childs,
PY - 2012
KW - Volume visualization
KW - parallel processing.
VL - 18
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Mark Howison, Brown University, Providence
E. Wes Bethel, Lawrence Berkeley National Laboratory, Berkeley
Hank Childs, Lawrence Berkeley National Laboratory, Berkeley
With the computing industry trending toward multi- and many-core processors, we study how a standard visualization algorithm, raycasting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with data sets as large as 12.2 trillion cells. The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.

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Index Terms:
Volume visualization, parallel processing.
Citation:
Mark Howison, E. Wes Bethel, Hank Childs, "Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 1, pp. 17-29, Jan. 2012, doi:10.1109/TVCG.2011.24
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