Simplifying the setup of simulations

Developing an intuitive framework to allow researchers to setup, configure and run simulation jobs, using different simulation packages and computing resources


Simulations are an invaluable tool in many disciplines, but the complexity of setting them up can make them difficult for non-experts to use. This project aims to provide a suite of tools that will make it straightforward to configure and run simulation jobs. By lowering the barrier of expertise needed, these tools have the potential to be used across academia and industry to facilitate the wider use of simulations.

Explaining the science

Fluid dynamics is one of the disciplines in which simulations are absolutely crucial, but the CPU resources needed to run them can often only be delivered on large computing clusters, or in the cloud. The middleware developed in this project makes it straightforward to adapt scripts and configuration such that the same interface is presented to the user, and the job will run reliably on any choice of backend.

Meanwhile, the frontend presents a simple and intuitive interface allowing users to choose parameters and submit simulation jobs, without needing to know all the complexities of the simulation package.

Project aims

This project involves the development of several software components. One of these is a middleware application with a streamlined interface that can be easily adapted to work with different simulator packages and different backend compute resources. Another component is an intuitive web frontend to allow users to configure and run their jobs, and to retrieve and visualise the output.

The goal is that someone with some knowledge of a simulation package would easily be able to specify and setup a use-case, including a set of parameters to be tuned, and then a non-expert would be able to set these parameters and run simulation jobs via the frontend.


This project is initially looking at use-cases in the field of fluid dynamics, but the software could equally be used in any discipline where compute-intensive simulations are run, such as medicine, physics and astronomy, mechanical engineering and others.

Read the Impact Story 'Making simulations simpler' to find out more about how the work and collaboration between the Turing, Imperial and UCL came about and its future potential.


Professor Omar Matar

Data-Centric Engineering Strategic Leader, The Alan Turing Institute & Vice-Dean (Education), Faculty of Engineering, Imperial College London

Researchers and collaborators

Contact info

[email protected]