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https://github.com/gapatino/Making-Your-Code-Faster
-Cython-and-parallel-processing-in-the-Jupyter-Notebook
Making Your Code Faster:
Cython and parallel processing
in the Jupyter Notebook
PyData DC 2016
Gustavo A. Patino
Department of Biomedical Sciences
Department of Neurology
Oakland University William Beaumont School of Medicine
Rochester, MI
https://github.com/gapatino/Making-Your-Code-Faster-Cython-and-parallel-processing-in-the-Jupyter-Notebook
Disclaimer
• No financial interests on any company or
package that will be mentioned
• Not a computer scientist
https://github.com/gapatino/Making-Your-Code-Faster-Cython-and-parallel-processing-in-the-Jupyter-Notebook
Problem description
• Using Euler’s method: y(n+1)=yn+(step_size*y’)
approximate the function y=x2 for a million
points
• Determine the minimum step size for the result
to be within 1e-5 of the correct answer at the last
point evaluated
• Note how a step size of 1 means we will evaluate
values of x between 0 and 1000000, while a step
sizeof 0.001 means that x ranges from 0 to 1000
https://github.com/gapatino/Making-Your-Code-Faster-Cython-and-parallel-processing-in-the-Jupyter-Notebook
https://github.com/gapatino/Making-Your-Code-Faster
-Cython-and-parallel-processing-in-the-Jupyter-Notebook

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