Scientific computing can be described as the field of study concerned with constructing mathematical models and quantitative analysis techniques to computationally analyze and solve scientific problems. Increasingly, the field also has to cope with how to deal with large amounts of data that may be involved. The UIS' Scientific Computing team can provide a range of assistance and resources in this area, e.g.:
- Programming advice across a number of languages, but especially C, C++, Fortran and Python.
- Numerical techniques, especially when applied using MATLAB or Numpy/Scipy.
- General algorithmic methods (searching, sorting, etc.).
- Distributed computing, e.g. using grids and clouds, but especially using HTCondor.
- Parallel programming, e.g. using MPI and OpenMP.
This list is not exhaustive, and it should be noted that scientific programming is not limited to what people in the physical sciences do, but includes the statistical analysis and modeling done in the arts and humanities. It does not always involve numbers, but includes such things as string manipulation (as in genome analysis) and methods of organising and querying your data. So if you would like to find out more about Scientific Computing, or would like to discuss a related computing problem or project, then please do get in touch.