Computational science (also scientific computing or scientific computation) is concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze and solve scientific and engineering problems. In practical use, it is typically the application of computer simulation and other forms of computation from numerical analysis and theoretical computer science to problems in various scientific disciplines.
The field is different from theory and laboratory experiment which are the traditional forms of science and engineering. The scientific computing approach is to gain understanding, mainly through the analysis of mathematical models implemented on computers.
Scientists and engineers develop computer programs, application software, that model systems being studied and run these programs with various sets of input parameters. In some cases, these models require massive amounts of calculations (usually floating-point) and are often executed on supercomputers or distributed computing platforms.
Numerical analysis is an important underpinning for techniques used in computational science.
Programming languages and computer algebra systems commonly used for the more mathematical aspects of scientific computing applications include R (programming language), TK Solver, MATLAB, Mathematica, SciLab, GNU Octave, Python (programming language) with SciPy, and PDL. The more computationally intensive aspects of scientific computing will often use some variation of C or Fortran and optimized algebra libraries such as BLAS or LAPACK.