Interactive Visualization of the Largest Radioastronomy Cubes

TL;DR

This paper introduces an interactive visualization framework for large 3D astronomical data cubes, leveraging heterogeneous CPU-GPU clusters to enable real-time rendering of datasets exceeding memory capacity.

Contribution

The authors present a novel distributed GPU-based volume rendering system that efficiently visualizes large-scale astronomical data cubes across multiple workstations.

Findings

Able to render a 26 GB data cube in under 0.3 seconds

System scales to datasets of terabyte size with appropriate hardware

Demonstrated on real astronomical survey data sets

Abstract

3D visualization is an important data analysis and knowledge discovery tool, however, interactive visualization of large 3D astronomical datasets poses a challenge for many existing data visualization packages. We present a solution to interactively visualize larger-than-memory 3D astronomical data cubes by utilizing a heterogeneous cluster of CPUs and GPUs. The system partitions the data volume into smaller sub-volumes that are distributed over the rendering workstations. A GPU-based ray casting volume rendering is performed to generate images for each sub-volume, which are composited to generate the whole volume output, and returned to the user. Datasets including the HI Parkes All Sky Survey (HIPASS - 12 GB) southern sky and the Galactic All Sky Survey (GASS - 26 GB) data cubes were used to demonstrate our framework's performance. The framework can render the GASS data cube with a maximum render time < 0.3 second with 1024 x 1024 pixels output resolution using 3 rendering workstations and 8 GPUs. Our framework will scale to visualize larger datasets, even of Terabyte order, if proper hardware infrastructure is available.