  Next generation astronomical surveys naturally pose challenges for
human-centred visualisation and analysis workflows that currently rely on the
use of standard desktop display environments. While a significant fraction of
the data preparation and analysis will be taken care of by automated pipelines,
crucial steps of knowledge discovery can still only be achieved through various
level of human interpretation. As the number of sources in a survey grows,
there is need to both modify and simplify repetitive visualisation processes
that need to be completed for each source. As tasks such as per-source quality
control, candidate rejection, and morphological classification all share a
single instruction, multiple data (SIMD) work pattern, they are amenable to a
parallel solution. Selecting extragalactic neutral hydrogen (HI) surveys as a
representative example, we use system performance benchmarking and the visual
data and reasoning (VDAR) methodology from the field of information
visualisation to evaluate a bespoke comparative visualisation environment: the
encube visual analytics framework deployed on the 83 Megapixel Swinburne
Discovery Wall. Through benchmarking using spectral cube data from existing HI
surveys, we are able to perform interactive comparative visualisation via
texture-based volume rendering of 180 three-dimensional (3D) data cubes at a
time. The time to load a configuration of spectral cubes scale linearly with
the number of voxels, with independent samples of 180 cubes (8.4 Gigavoxels or
34 Gigabytes) each loading in under 5 minutes. We show that parallel
comparative inspection is a productive and time-saving technique which can
reduce the time taken to complete SIMD-style visual tasks currently performed
at the desktop by at least two orders of magnitude, potentially rendering some
labour-intensive desktop-based workflows obsolete.
