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Parallel computation of adaptive wavelet-based 2D flood models

  • Full or part time
  • Application Deadline
    Monday, July 01, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Computer Science graduates are invited to apply for this fully-funded 3.5 year PhD studentship in the Department of Civil and Structural Engineering. This is an exciting opportunity for you to apply and develop your skills within an interdisciplinary project, which aims to design and execute a parallel implementation of an existing flood simulator. The project also includes regular engagement with flood model developers and consultants, and annual attendance of academic conferences.

Project description
Many flood models rely on speed-up of parallelism to accommodate fast simulations over large domain [1]. Although parallelism has become established in flood modelling, it is often achieved a fixed mesh in order to alleviates many issues in both parallel computing science and practical modelling, e.g. domain decomposition, synchronized data distribution across many processors, wetting and drying treatment [2,3,4].

You will join the SEAMLESS-WAVE project team to build on their developing adaptive wavelet-based flood model. Wavelet adaptivity provides 35-50 speedup over the fixed mesh version without parallelisation. However, it entails constant transfer of modelled-data at different scales and changes in mesh. This form a non-standard challenge [5] to achieved parallelisation, which will be tackled in this PhD, together with the standard challenges [2,3,4] to ultimately produce a parallelised adaptive wavelet based flood model.

Phase 1- Understanding and analysing (multi)wavelet data (de)compression and the adaptive numerical flow solver. You will work closely with the model developers to provide code efficiency analysis report and documented plan(s) of how the code operations can be reordered in favour of parallel computing. Output of this phase will be an optimised code implementation alongside a documented algorithmic work-plan.

Phase 2- Coding of a parallelised wavelet-based flood model. Informed by phase 1, a choice of where to implement the parallel version will be made. One possible route would be to use PGI Fortran compiler with a view to achieve the parallelisation on GPUs. This choice is compatible with the current Fortran 2003 implementation of the flood model and allows flexibility for parallelization using any other route (i.e. migrating computational heavy aspects of the code to dedicated CUDA routines). The uniform and adaptive mesh versions will be parallelised within same code structure to allow quantifying the efficiency speed-up gains against overheads of both parallelisation and mesh adaptivity.

Phase 3- Application to large-scale real-study sites. By this phase, the parallelised adaptive flood simulator will be validated in reproducing realistic flood scenarios over very large domains. A critical review of existing many case studies will be carried out to select up to four tests featured by large spatial coverage, fine resolution terrain data, and availability of reference data. Set up and runs for these case studies will be performed to identify the extent to which speed-up scaling is maximised.

The Candidate
Suitable for candidates holding or anticipating award of a Distinction/Merit MSc, or 1st/2.1 undergraduate degree in computer sciences discipline. The suitable candidate is desired to have a good mathematical background and to able to work in a team of mathematicians and engineers.

The successful candidate must start by February 2020.

Funding Notes

UK/resident EU applicants: Fully funded PhD plus maintenance award (£14,553 pa in 2017/18) for three and a half years.
EU applicants: Non-resident EU students eligible for fees only award.

How good is research at University of Sheffield in Civil and Construction Engineering?

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

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