I/O Strategies for Parallel Rendering of Large Time-Varying Volume Data
Hongfeng Yu, Kwan-Liu Ma, Joel Welling
Eurographics Symposium on Parallel Graphics and Visualization, 2004, pp. 31--40.
Abstract: This paper presents I/O solutions for the visualization of time-varying volume data in a parallel and distributed computing environment. Depending on the number of rendering processors used, our I/O strategies help signifi- cantly lower interframe delay by employing a set of I/O processors coupled with MPI parallel I/O support. The targeted application is earthquake modeling using a large 3D unstructured mesh consisting of one hundred millions cells. Our test results on the HP/Compaq AlphaServer operated at the Pittsburgh Supercomputing Center demonstrate that the I/O strategies effectively remove the I/O bottlenecks commonly present in time-varying data visualization. This high-performance visualization solution we provide to the scientists allows them to explore their data in the temporal, spatial, and visualization domains at high resolution. This new high-resolution explorability, likely not presently available to most computational science groups, will help lead to many new insights.
@inproceedings{Yu:2004:ISF,
author = {Hongfeng Yu and Kwan-Liu Ma and Joel Welling},
title = {I/O Strategies for Parallel Rendering of Large Time-Varying Volume Data},
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
pages = {31--40},
year = {2004},
}
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