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"""Calculate statistics on the digits of pi in parallel.
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This program uses the functions in :file:`pidigits.py` to calculate
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the frequencies of 2 digit sequences in the digits of pi. The
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results are plotted using matplotlib.
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To run, text files from http://www.super-computing.org/
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must be installed in the working directory of the IPython engines.
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The actual filenames to be used can be set with the ``filestring``
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variable below.
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The dataset we have been using for this is the 200 million digit one here:
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ftp://pi.super-computing.org/.2/pi200m/
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"""
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from IPython.kernel import client
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from matplotlib import pyplot as plt
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import numpy as np
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from pidigits import *
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from timeit import default_timer as clock
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# Files with digits of pi (10m digits each)
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filestring = 'pi200m-ascii-%(i)02dof20.txt'
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files = [filestring % {'i':i} for i in range(1,16)]
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# Connect to the IPython cluster
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mec = client.MultiEngineClient(profile='mycluster')
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mec.run('pidigits.py')
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# Run 10m digits on 1 engine
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mapper = mec.mapper(targets=0)
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t1 = clock()
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freqs10m = mapper.map(compute_two_digit_freqs, files[:1])[0]
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t2 = clock()
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digits_per_second1 = 10.0e6/(t2-t1)
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print "Digits per second (1 core, 10m digits): ", digits_per_second1
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# Run 150m digits on 15 engines (8 cores)
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t1 = clock()
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freqs_all = mec.map(compute_two_digit_freqs, files[:len(mec)])
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freqs150m = reduce_freqs(freqs_all)
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t2 = clock()
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digits_per_second8 = 150.0e6/(t2-t1)
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print "Digits per second (8 cores, 150m digits): ", digits_per_second8
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print "Speedup: ", digits_per_second8/digits_per_second1
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plot_two_digit_freqs(freqs150m)
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plt.title("2 digit sequences in 150m digits of pi")
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