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1.4: Ideas needed to do Effective Scientific Computing

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Scientific Computing is generally used to solve problems in Mathematics and various Science fields. There are a number of important things that you need to know to solve problems effectively.

  • Find/develop code that runs quickly. Everyone wants the answer as soon as possible. However, if you write some code that doesn’t take long to develop and returns the correct answer in a few seconds, it probably doesn’t matter how efficient the algorithm is. However, if it takes a few hours to run, you probably want to investigate your solution algorithm.
  • Find/develop code that uses an appropriate amount of memory. Another important aspect is that of memory consumption. It’s not hard to find datasets these days that are 1TB or more in size, however few desktop/laptop machines have more than 16 or 32Gb of RAM, so you can’t load the entire file into memory. Such a dataset would need to be processed in chunks.
  • Make sure you have known solutions/unit tests How do you know that your solution is correct? It is important to have relatively simple cases that you can test your code on before solving more complex things.

This page titled 1.4: Ideas needed to do Effective Scientific Computing is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by Peter Staab.

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