SC20 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Integrated Micro-Scale Modeling and Urban Environment Service Cyberinfrastructure for Smart Cities

Workshop:Urgent HPC: HPC for Urgent Decision Making

Authors: Akshara Kaginalkar (Centre for Development of Advanced Computing, India)

Abstract: Lightning talk: Rapid urbanization is contributing to natural environment stress, making large populationa vulnerable to extreme weather disasters risks. Extreme events such as rainfall, floods, heat waves and pollution have incremental complexities with cascading health and economy impacts. Each city has specific characteristics in terms of its geography, climate, socio-economic conditions and city infrastructure. Science-driven timely city operations and planning decisions are crucial in urban disaster management.

City environment has a large spatio-temporal variability. Capturing the neighborhood scale processes needs high resolution modeling. These predictions are computationally expensive due to complex physics parametrization, large scale data assimilation and multi-model ensemble executions, requiring a large amount of HPC resources. Addressing these needs, we have initiated NSM_urban, a consortia program of researchers, municipalities, policy makers and HPC developers for Indian cities. Under its aegis, we are developing Urban Environment Science to Society (UES2S): an HPC-cloud cyberinfrastructure with multi-sector modeling and city services platform. It promotes green computing with shared resources and is adaptable to other world cities, especially developing countries.

UES2S has a timely disaster management decision support system with neighborhood scale model simulation scenarios expert system, modeling as a service (MaaS) and data as a service (DaaS) HPC-cloud services translating model output to city user tailored services with meteorology, hydrology, air quality and CFD models, and value-added real-time data fusion tools using numerical models, big data and machine learning methods

We share our collaborative development experience and UES2S architecture in the lightning talk.


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