Scalable Lagrangian-Based Attribute Space Projection for Multivariate Unsteady Flow Data

Hanqi Guo, Fan Hong, Qingya Shu, Jiang Zhang, Jian Huang, Xiaoru Yuan
2014 2014 IEEE Pacific Visualization Symposium  
In this paper, we present a novel scalable approach for visualizing multivariate unsteady flow data with Lagrangian-based Attribute Space Projection (LASP). The distances between spatiotemporal samples are evaluated by their attribute values along the advection directions in the flow field. The massive samples are then projected into 2D screen space for feature identification and selection. A hybrid parallel system, which tightly integrates a MapReduce-style particle tracer with a scalable
more » ... ithm for the projection, is designed to support the large scale analysis. Results show that the proposed methods and system are capable of visualizing features in the unsteady flow, which couples multivariate analysis of vector and scalar attributes with projection.
doi:10.1109/pacificvis.2014.15 dblp:conf/apvis/GuoHSZHY14 fatcat:3dq2v6owkfbllpcjochf3fdj6q