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Home > Computer Articles > Scientific Computing

Resources For Scientific Computing

Scientific computing is the field of computational science. Scientists construct mathematical models geared to analyze and solve scientific problems dealing with such issues as data and numerical analysis. Scientific computing involves the use of a computer to apply a method of solving a problem. This is called a scientific tool or model.

This model helps you answer certain questions about issues related to science. Science is about experimentation or testing a hypothesis in a controlled study. It is also about observation and prediction. Computational science has its hand in all three: experimental, observational, and theoretical science. Yet these three aspect hold a slightly different meaning when used in scientific computing.

Theory tends to be broad in assumption while scientific computing is exact. Observation and experimentation are about generally about nature, however, in computational science, they are about models of nature that aid in understanding the world. Think of how statistical data helps scientists understand that crime is worse in one section of a city than another or how many people die of lung cancer that smoked. You can see that data analysis is used rather than the scientific method.

History of Computational Science

  • The First Supercomputer: Changing a program in ENIAC took at least two days. ENIAC was the first supercomputer to attempt computational science.
  • History Scientific Computing: Limited history from hand-wiring programs in ENIAC in 1945 to the 1998 Nobel Prize in Chemistry for Computational Science.
  • Numerical Analysis Timeline: Includes oral histories, presentations, and links with .pdfs on discoveries and applications of numerical analysis and scientific computing.
  • Numerical Method Timeline: Brief historical timeline of computational science and high performance computing 1940-2000. Includes numerical method and simulation.
  • Top 500 Supercomputer Sites: Search for list and sub-lists of the top 500 supercomputer sites worldwide.

Components of Scientific Computing

  • Scientific Data Management Center: Scientific data is complex and overwhelming. Part of computational science deals with managing that data in file systems.
  • Mathematical Modeling: Guides to reverse engineering, discrete and continuous models, and probability models.
  • Farming Overview: The computational science infrastructure in pictorial format.
  • SimScience: How simulations help us understand relationships such as cell membranes, soap bubbles, space and time.
  • Computational Complexity: Colloquium exists "for the rapid and widespread interchange of ideas, techniques, and research in computational complexity."
  • Simulations: Article about how simulations explained DNA nanotube unexpected translocation.
  • Numerical Simulations: Kevlin-Helmholtz instability using PPM. Five terabytes of data was collected, analyzed, and visualized.
  • High Performance Collaboration: The HPC2 recently hosted "The Everyday Impact of High Performance Computing." You can read the .pdf event files presented at the seminar.
  • The Latest in Scientific Computing: Applications, research, and latest data analyses.
  • Beginning Python: An intensive tutorial of the Python language (used in scientific computing) for researchers. No experience needed, but basic programming is desirable.
  • Scientific Discovery through Advanced Computing: Applications in physics, climate, fusion energy, and materials science.
  • Free Fortran Download: Book of numerical recipes, Fortran 90, scientific parallel computing.

Applications of Computational Science

  • Computational Analysis of Hockey: Development of a system of how hockey is played and how to use that knowledge to boost performance.
  • Systems Genetics: Integrative computational science program to advance understanding in how genes influence common disease.
  • Breathing Lessons: Small Airway Fluid Dynamics project. How computational analysis is aiding medicine.
  • Game Theory: Can economic behavior be speculated on by game theory?
  • Search Engine Analytics: Computational science applications extends to numerical analytics such as Google site analytics, data patterns, and tracking.
  • Analyzing Culture: How computational science aids in analyzing culture through analytics and simulations.
  • Joint Institute of Computational Sciences: Opened to further computational modeling, simulations, and use of the Oak Ridge National Lab's petascale-plus supercomputers. The University of Tennessee and the ORNL jointly operate to further such investigations as tracking HIV-1 protease.
  • Mapping the Human Genome: The Human Genome project is one of the most famous computational science projects ever completed.

We have articles on the History Of The Computer, scientific computing, and software development, plus reviews of netbooks, desktops, and Refurbished Laptops.

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