A Study of Parallel Particle Tracing for Steady-STate and Time-Varying Flow Fields

TitleA Study of Parallel Particle Tracing for Steady-STate and Time-Varying Flow Fields
Publication TypeConference Paper
Year of Publication2011
AuthorsPeterka, T, Ross, RB, Nouanesengsy, B, Lee, T-Y, Shen, H-W, Kendall, W, Huang, J
Conference NameProceedings of Parallel & Distributed Processing Symposium
Date Published05/2011
Conference LocationAnchorage
Other NumbersANL/MCS-P1828-0111
Abstract

Particle tracing for streamline and pathline generation is a common method of visualizing vector fields in scientific data, but it is difficult to parallelize efficiently because of demanding and widely varying computational and communication loads. In this paper we scale parallel particle tracing for visualizing steady and unsteady flow fields well beyond previously published results. We configure the 4D domain decomposition into spatial and temporal blocks that combine in-core and out-of-core execution in a flexible way that favors faster run time or smaller memory. We also compare static and dynamic partitioning approaches. Strong and weak scaling curves are presented for tests conducted on an IBM Blue Gene/P machine at up to 32K processes using a parallel flow visualization library that we are developing. Datasets are derived from computational fluid dynamics simulations of thermal hydraulics, liquid mixing, and combustion.

PDFhttp://www.mcs.anl.gov/papers/P1828.pdf