Adjusted text on describing benchmarking procedure.

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Craig Warren
2016-03-17 10:50:52 +00:00
父节点 cafb0f0864
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@@ -27,8 +27,8 @@ The following simple models (found in the ``tests/benchmarking`` sub-package) ca
Using the following steps to collect and report benchmarking results for each of the models: Using the following steps to collect and report benchmarking results for each of the models:
1. Run gprMax in benchmarking mode, e.g. ``python -m gprMax tests/benchmarking/bench_100x100x100.in -benchmark`` 1. Run gprMax in benchmarking mode, e.g. ``python -m gprMax tests/benchmarking/bench_100x100x100.in -benchmark``
2. Use the ``plot_benchmark`` module to create plots of the execution time and speed-up, e.g. ``python -m tests.benchmarking.plot_benchmark tests/benchmarking/bench_100x100x100.npz``. You will need to enter some machine identification information in the module. 2. Use the ``plot_benchmark`` module to create plots of the execution time and speed-up, e.g. ``python -m tests.benchmarking.plot_benchmark tests/benchmarking/bench_100x100x100.npz``. You will be prompted to enter information to describe your machine, number and type of CPU/cores, and operating system.
3. Commit the Numpy archive and plot file to the GitHub repository 3. Share your data by commiting the Numpy archive and plot file to our GitHub repository, or by uploading them to a post in our Google group (http://www.gprmax.com/forum.shtml).
Results Results
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