Abstract
Smarter cities and infrastructure are essential if the world is to respond effectively to the critical challenges it faces. As of 2008, and for the first time in human history, more than half of the world's population now live in cities. Yet cities increasingly need to be able to do more with less, to provide for the well-being of their citizens in a truly sustainable way. City-scale simulations are becoming a possibility with advancements in the computing hardware and software technologies. Recent advancements in distributed scaling using Apache Spark is exemplified through a case-study on simulating the traffic flow behaviour of London at per-hour time resolution. The case-study on the response of ground and structures in central Tokyo shows the advancements in multigrid techniques and Finite Element simulations. This paper discusses the advancements and challenges in high-performance computing (hardware, algorithms, software, and visualisation techniques) in achieving the possibility of real-time city-scale simulations.
Highlights
Smarter cities and infrastructure are essential if the world is to respond effectively to the critical challenges it faces
The case-study on the response of ground and structures in central Tokyo shows the advancements in multigrid techniques and Finite Element simulations
The purpose of the Agent-based modelling (ABM) tool is to capture the complex city-scale response from individual agent behaviours. Macroscale events such as earthquakes influence the weights of the edges on a graph network, which in turn affect the behaviour of individual agents, changing the response of a city
Summary
The twenty-first century is witnessing a rapid rise of urbanisation in both the developed and the developing worlds. The purpose of the ABM tool is to capture the complex city-scale response from individual agent behaviours. The real-time sampling feature allows for querying and updating individual agent behaviours in a scenario testing of global impacts, such as in understanding the resilience of a city to an earthquake scenario Another example of a city-scale computing tool is the highresolution finite-element modelling of ground motion to analyse the response of structures during an earthquake. As compilers become efficient in identifying vectorisable regions of codes, there is an increased focus in compiler autoparallelisation Parallel programming frameworks such as Kokkos and Charm++ focus on improving performance portability across multiple shared and distributed memory architectures (Edwards et al, 2014; Kale and Krishnan, 1993). As the computing jobs become more complex, resource management and scheduling tools such as Yarn and Mesos become increasingly relevant
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
