I/O Strategies for Parallel Rendering of Large Time-Varying Volume Data

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.