Paper Info
Title
End-to-End Study of Parallel Volume Rendering on the IBM Blue Gene/P
Abstract
In addition to their role as simulation engines, modern supercomputers can be harnessed for scientific visualization. Their extensive concurrency, parallel storage systems, and high-performance interconnects can mitigate the expanding size and complexity of scientific datasets and prepare for in situ visualization of these data. In ongoing research into testing parallel volume rendering on the IBM Blue Gene/P (BG/P), we measure performance of disk I/O, rendering, and compositing on large datasets, and evaluate bottlenecks with respect to system-specific I/O and communication patterns. To extend the scalability of the direct-send image compositing stage of the volume rendering algorithm, we limit the number of compositing cores when many small messages are exchanged. To improve the data-loading stage of the volume renderer, we study the I/O signatures of the algorithm in detail. The results of this research affirm that a distributed-memory computing architecture such as BG/P is a scalable platform for large visualization problems.
Year
DOI
Venue
2009
10.1109/ICPP.2009.27
ICPP
Keywords
Field
DocType
data visualisation,distributed memory systems,parallel architectures,parallel machines,rendering (computer graphics),I/O signatures,IBM Blue Gene/P,data visualization,direct-send image compositing stage,distributed-memory computing architecture,parallel storage systems,parallel volume rendering,scientific visualization,supercomputer,Distributed scientific visualization,image compositing,parallel I/O,parallel volume rendering
Parallel rendering,Volume rendering,Supercomputer,Computer science,Visualization,Parallel computing,Parallel I/O,Rendering (computer graphics),Scientific visualization,Compositing
Conference
Citations 
PageRank 
References 
25
1.58
17
Authors
5
Name
Order
Citations
PageRank
Tom Peterka153149.78
Hongfeng Yu261139.24
Robert Ross32717173.13
Kwan-Liu Ma45145334.46
Rob Latham523611.68