Scalable desktop visualisation of very large radio astronomy data cubes

We describe a scalable, hierarchical approach to 3D visualisation of very large spectral data cubes to enable rapid visualisation of large data files on standard desktop hardware. Our hierarchical approach, embodied in the AstroVis prototype, aims to provide a means of viewing large datasets that do not fit into system memory. The focus is on rapid initial response: our system initially rapidly presents a reduced, coarse-grained 3D view of the data cube selected, which is gradually refined. The user may select sub-regions of the cube to be explored in more detail, or extracted for use in applications that do not support large files. We thus shift the focus from data analysis informed by narrow slices of detailed information, to analysis informed by overview information, with details on demand. Our hierarchical solution to the rendering of large data cubes reduces the overall time to complete file reading, provides user feedback during file processing and is memory efficient. This solution does not require high performance computing hardware and can be implemented on any platform supporting the OpenGL rendering library.