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Complex flow simulations are conventionally performed on HPC clusters.However, the limited availability of HPC resources and steep learning curve ofexecuting on traditional supercomputer infrastructure has drawn attentiontowards deploying flow simulation software on the cloud. We showcase how acomplex computational framework -- that can evaluate COVID-19 transmission riskin various indoor classroom scenarios -- can be abstracted and deployed oncloud services. The availability of such cloud-based personalized planningtools can enable educational institutions, medical institutions, public sectorworkers (courthouses, police stations, airports, etc.), and other entities tocomprehensively evaluate various in-person interaction scenarios fortransmission risk. We deploy the simulation framework on the Azure cloudframework, utilizing the Dendro-kT mesh generation tool and PETSc solvers. Thecloud abstraction is provided by RocketML cloud infrastructure. We compare theperformance of the cloud machines with state-of-the-art HPC machine TACCFrontera. Our results suggest that cloud-based HPC resources are a viablestrategy for a diverse array of end-users to rapidly and efficiently deploysimulation software.

Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources