IPython magic for parallel profiling
Project description
A tool for measuring serial and parallel execution, and comparing the results. Provides an IPython magic %ptime. This can be useful for measuring the benefits of parallelizing code, including measuring the effect of the Global Interpreter Lock (GIL).
Example
In [1]: %load_ext ptime
In [2]: import numpy as np
In [3]: x = np.ones((5000, 10000))
In [4]: %ptime x + x
Total serial time: 0.42 s
Total parallel time: 0.25 s
For a 1.67X speedup across 2 threads
In [5]: %ptime -n4 x + x # use 4 threads
Total serial time: 0.82 s
Total parallel time: 0.31 s
For a 2.60X speedup across 4 threads
In [6]: res = %ptime -o x + x # Get the result
Total serial time: 0.41 s
Total parallel time: 0.25 s
For a 1.66X speedup across 2 threads
In [7]: res.speedup
Out[7]: 1.6610825669011922
In [8]: %%ptime # Use as a cell magic
...: x = np.ones((5000, 10000))
...: y = x + x
...:
Total serial time: 0.72 s
Total parallel time: 0.47 s
For a 1.54X speedup across 2 threadsInstall
This package is available via pip:
pip install ptimeRelease history Release notifications | RSS feed
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ptime-0.0.1.tar.gz
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