Scientific Computing, also known as Computational Science is the branch of study that involves the use of computers for solving and analyzing scientific and engineering problems. Scientific Computing also involves construction of numerical solution methods and mathematical models. In other words, varied forms of computation and application of computer stimulation is used in different scientific disciplines.
Scientific Computing is distinctly different from Computer Science, Engineering and other forms of traditional science. The Scientific Computing enables to understand especially by analyzing mathematical models that are implemented on the computers.
Scientific computation is usually studied with the aid of applied mathematics and a computer science, engineering or science program. At some educational institutions one can earn a ‘minor' specialization in scientific computation within some other program. Besides this one can also acquire a master's or bachelor's program in the subject of scientific computation, computational science, computational engineering and general engineering.
The following are the applications of scientific computing –
- Numerical analysis
- Numerical simulations
- Reconstructing and understanding known events (e.g. tsunamis, earthquakes and other natural calamities).
- Predicting future or unseen situations
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- Data Analysis and Model fitting (e.g. computational linguistics and oil exploration geophysics)
- Optimization (e.g., manufacturing and technical processes).
- Methods and algorithms
Sometimes the mathematical aspects of scientific computing require the use of various Programming Languages. These Programming Languages that are used for scientific computing include MATLAB, Num-Python, Sci-Python, GNU Octave, UCINet, FORTRAN and PDL. However the greater computationally-intensive parts of scientific computing generally utilize some variations of FORTRAN or C.
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