  Background: Photo-realistic terapixel visualization is computationally
intensive and to date there have been no such visualizations of urban digital
twins, the few terapixel visualizations that exist have looked towards space
rather than earth. Objective: our aims are: creating a scalable cloud
supercomputer software architecture for visualization; a photo-realistic
terapixel 3D visualization of urban IoT data supporting daily updates; a
rigorous evaluation of cloud supercomputing for our application. Method: we
migrated the Blender Cycles path tracer to the public cloud within a new
software framework designed to scale to petaFLOP performance. Results: we
demonstrate we can compute a terapixel visualization in under one hour, the
system scaling at 98% efficiency to use 1024 public cloud GPU nodes delivering
14 petaFLOPS. The resulting terapixel image supports interactive browsing of
the city and its data at a wide range of sensing scales. Conclusion: The GPU
compute resource available in the cloud is greater than anything available on
our national supercomputers providing access to globally competitive resources.
The direct financial cost of access, compared to procuring and running these
systems, was low. The indirect cost, in overcoming teething issues with cloud
software development, should reduce significantly over time.
