Petascale Cloud Supercomputing for Terapixel Visualization of a Digital Twin
TL;DR: 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 this application.
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Abstract: 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.
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Figures
TABLE 2 TERAPIXEL TASK PROPERTIES 
TABLE 3 TERASCOPE PERFORMANCE METRICS 
TABLE 4 TERAPIXEL NORMALISED PERFORMANCE DATA (K80) 
Fig. 4. Evaluating the scalability of the gigapixel computation on NC6 K80 nodes, speedup as a function of the number GPU nodes from 1 to 128 nodes scales, as expected, sub-linearly due to low task load. 
Fig. 5. Evaluating the scalability of the terapixel computation on NC6 K80 nodes, plotting speedup ratio as a function of the number of GPU nodes from 64 to 128 nodes, the bars show the +/-8.5% range of variability we measured in repeated runs. 
TABLE 6 TERASCOPE SYSTEM ENERGY USE
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