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@@ -47,7 +47,7 @@ When the notebook opens in your browser, you will see the **Notebook Dashboard**
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For more information please refer to [Jupyter documentation](https://docs.jupyter.org/en/latest/running.html)
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## Benchmarks
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Data Parallel Extensions for Python provide a set of benchmarks illustrating different aspects of implementing the performant code with Data Parallel Extensions for Python.
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Data Parallel Extensions for Python provide a set of [benchmarks](https://github.com/IntelPython/dpbench) illustrating different aspects of implementing the performant code with Data Parallel Extensions for Python.
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Benchmarks represent some real life numerical problem or some important part (kernel) of real life application. Each application/kernel is implemented in several variants (not necessarily all variants):
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- Pure Python: Typically the slowest and used just as a reference implementation
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-`numpy`: Same application/kernel implemented using NumPy library
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