Accelerating In-transit Isosurface Generation With Topology Preserving Compression

TL;DR

This paper presents a topology-preserving lossy compression framework that accelerates in-transit isosurface generation, enabling up to 4x faster visualization workflows for scientific data analysis.

Contribution

It introduces a novel Compressed Hierarchical Representation with topology preservation to improve in-transit isosurface generation speed.

Findings

Achieves up to 4x speedup in visualization workflows

Maintains isosurface fidelity through topology-preserving compression

Enhances real-time scientific data analysis capabilities

Abstract

Data visualization through isosurface generation is critical in various scientific fields, including computational fluid dynamics, medical imaging, and geophysics. However, the high cost of data sharing between simulation sources and visualization resources poses a significant challenge. This paper introduces a novel framework that leverages lossy compression to accelerate in-transit isosurface generation. Our approach involves a Compressed Hierarchical Representation (CHR) and topology-preserving compression to ensure the fidelity of the isosurface generation. Experimental evaluations demonstrate that our framework can achieve up to 4x speedup in visualization workflows, making it a promising solution for real-time scientific data analysis.