Topic:Scientific computing

This is a placeholder page for Scientific Computing, and is far from being complete.

Scientific Computing is a Department under the School of Computer Science. This will contain lessons on Numerical Algorithms, Modelling and Simulation and Bioinformatics.

Introduction

Scientific Computing is the science of solving problems with computers. The problems themselves usualy arise from other disciplines such as Mathematics, Engineering, Biology, Physics, Chemistry and other natural sciences. As a consequence, Scientific Computing is interdisciplinary by nature. The dividing line between Scientific Computing and the sciences from which its problems originate is best described by what Scientific Computing is not -- and what it is.

• Computing Pi to the 1'000'000th digit is not Scientific Computing. Developing algorithms to efficiently compute $\pi$ to any precision is Scientific Computing.
• Running a Molecular Dynamics simulation with 1'000'000 atoms for 100 nanoseconds is not Scientific Computing. Developing models and algorithms to efficiently simulate large particle systems is Scientific Computing.
• Computing the eigenvalues of a 1'000 x 1'000 dense, complex matrix is not Scientific Computing. Developing efficient and accurate methods to determine the eigevalues of any large, dense, complex matrix is Scientific Computing.
• Running an all-against-all sequence alignment of every genome known is not Scientific Computing. Developing realistic and efficient models for sequence evolution is Scientific Computing.

The line between Scientific Computing and the sciences from which its problems are derived is drawn between interest in the methods used to solve problems and the solution of the problems themselves. In other words, all scientists use computers, but very few do Scientific Computation.

Courses

This is just a suggestion of what courses should be offered in this Department. The actual content will probably depend more on what courses are actually implemented.

The Courses in Scientific Computing are divided into three main branches, each containing specific courses. It is recommended that you follow the courses within each main branch in the order presented. The main branches themselves are independent. Should dependencies accross branches arise, they will be indicated at the top of each course.

Numerical Algorithms (See also Numerical Analysis.) Finite Arithmetic Interpolation and Extrapolation Least-Squares Fitting Root Finding in one Dimension Root Finding in many Dimensions Numerical Integration and Differentiation Numerical Integration of ODEs

Modelling and Simulation Continuous Modelling Finite Elements and Volumes Particle Methods Machine Learning

Bioinformatics Evolutionary Models and Sequence Alignment Phylogenetic Trees Structure and Function Prediction Functional Genomics Systems Biology

Active Participants

The histories of Wikiversity pages indicate who the active participants are. If you are an active participant in this department, you can list your name here (this can help small departments grow and the participants communicate better; for large departments a list of active participants is not needed).

• Pedro.Gonnet 08:23, 9 October 2006 (UTC)

See also

• Portal:Computer Science
• Portal:Science
• School:Computer science
• Topic:Quantum computing
• Topic:Parallel computing
• Topic:Computer engineering
• Topic:Applied computer science
• Topic:Open source science
• Efficiency in Computing Project
• Quantum computing
• Integrating commercial computing packages
• Wikiversity Distributed Virtual Supercomputer
• Screensaver Project
• Introduction to Computer Science