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A simple, automated, and very flexible scalability test environment designed for your computer or cluster

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ScalaBee

A simple automated scalability test environment designed for your computer or cluster

Sample Output

Demo Doccou alphaDemo Doccou alpha

How to Use

Usage

  • Arguments

    scalaBee.py [+h] [+nTe numberOfTests] Prog Arg [Arg ...]

Examples

  • Generic example:

   Let's say your program has the arguments strutured like this:

```bash
myProgram -numberOfThreads=X -problemSize=Y -otherArg=file.txt
```
In this example, if you want to use 8 threads and the problem size is 10 you would execute

```bash
myProgram -numberOfThreads=8 -problemSize=10 -otherArg=file.txt
```

   Now let's say you want to check this program's speedup and efficiency with 1, 2, 4, 8, 16 threads and with problem sizes 10, 100, 1000. To do this using Scalabee, simply type

```bash
scalaBee.py myProgram -numberOfThreads={t16} -problemSize={p{10,100,1000}} -otherArg=file.txt
```

   If you want to run each combination multiple times to get a better time average (let's say 20 times) simply add the option:

```bash
+nTe 20 
```
Also note that it is optional to indicate the problem size.

Dependencies

  • This project depends on Matplotlib and PrettyTable. To install them, use the command:

    pip install PrettyTable matplotlib

Bug Reports & Feature Requests

You can help by reporting bugs, suggesting features, reviewing feature specifications or just by sharing your opinion. Use GitHub Issues for all of that.

Contributing

  1. Fork the project.
  2. Create a branch for your new feature.
  3. Test your code.
  4. Submit a pull request.

All pull requests are welcome !

Authors

This project was develloped by Daniel Holanda.

License

This project uses the MIT license. See LICENSE for more details.

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A simple, automated, and very flexible scalability test environment designed for your computer or cluster

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