High Performance Computing for City-Scale Modelling and Simulations
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Publication Date
2017-12-01Journal Title
Smart Infrastructure and Construction
ISSN
2397-8759
Publisher
ICE Publishing
Volume
170
Issue
4
Pages
80-85
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Soga, K., Casey, G., Soundararajan, K., & Zhao, B. (2017). High Performance Computing for City-Scale Modelling and Simulations. Smart Infrastructure and Construction, 170 (4), 80-85. https://doi.org/10.1680/jsmic.17.00026
Abstract
The 21st Century is witnessing a rapid rise of urbanization both in the developed and the developing world. Cities increasingly need to be able to do more with less in order to provide for the well-being of their citizens in a sustainable way. The promise of Smart City is an emerging ability to understand, to respond to, and to shape human activity at urban population and geographic scales so that a more agile, adaptive, and
sustainable urban environment can be created (see Batty et al., 2012; Caragliu et al., 2011; Chourabi et al., 2012; Su et al., 2011 for early adoption of Smart City). To be effective, this requires the predictive power of data-driven modelling and city-scale computational simulations. Recently city-scale simulations are becoming possible thanks to a surge of development in the high-performance computing (HPC) domain
including advanced hardware, computational and algorithmic techniques such as domain decomposition across multi-GPUs and multigrid techniques. Advanced high performance computing systems (a billion billion calculations per second) are now becoming available to performance city-scale simulations with micro-scale models of
an individual objective (structure, people, vehicle, etc.) (e.g. Sánchez-Medina et al., 2010; Hori, 2011; Zia et al., 2012; Wijerathne et al., 2013; Pijanowski et al., 2014; Yoshimura et al., 2016; Johansen et al., 2017; Lu and Guan., 2017)
Sponsorship
Engineering and Physical Sciences Research Council (EP/I019308/1)
EPSRC (1357298)
Identifiers
External DOI: https://doi.org/10.1680/jsmic.17.00026
This record's URL: https://www.repository.cam.ac.uk/handle/1810/273155
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