The use of mathematical Modelling, Simulation and Optimisation (MSO) methods have proven as effective tools for solving many real problems by the prediction of situations to optimize and control them (mainly in fields such as science, technology, industry and public service). These methods are highly complex and are typically required the most modern tools of ICT including high performance computing and access to big data bases and usually need support of skilled experts, which often are not available, in particular in small and medium enterprises. Most MSO techniques used are based on common high level numerical computing environments such as Matlab, or software libraries such as PETSc or packages on top of software libraries such as FEniCS:
Ensuring fast prototyping and scalability of the resulting codes are conflicting objectives for these software toolkits, but such conflict needs to be solved quite often;
Ideal solution processes need fast MSO prototyping, parallel scalability and ease of deployment to a suitable high performance computing (HPC) hardware for the development and running the applications, but this is not available yet;
The (affordable) compute capacity is the major limitation on the performance of the mathematical frameworks, so it is vital to be able to access the optimal solution.
The major objective of MSO4SC is to construct an e-infrastructure that provides, in a user-driven, integrative way, tailored access to the necessary services, resources and even tools for the fast prototyping, providing the service producers with the mathematical frameworks as well. The e-infrastructure consists of an integrated MSO application catalogue containing models, software, validation and benchmark and the MSOcloud: a user friendly cloud infrastructure for selected MSO applications and developing frameworks from the catalogue. This will reduce the ‘time-to-market’ for consultants working in the above-mentioned societal challenges.