view tests/testnumpy.py @ 7:9079a9f7c4cf

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"""
Benchmark script to be used to evaluate the performance improvement of the MKL
"""

import os
import sys
import timeit

import numpy
from numpy.random import random

def test_eigenvalue():
    """
    Test eigen value computation of a matrix
    """
    i = 500
    data = random((i,i))
    result = numpy.linalg.eig(data)

def test_svd():
    """
    Test single value decomposition of a matrix
    """
    i = 1000
    data = random((i,i))
    result = numpy.linalg.svd(data)
    result = numpy.linalg.svd(data, full_matrices=False)

def test_inv():
    """
    Test matrix inversion
    """
    i = 1000
    data = random((i,i))
    result = numpy.linalg.inv(data)

def test_det():
    """
    Test the computation of the matrix determinant
    """
    i = 1000
    data = random((i,i))
    result = numpy.linalg.det(data)

def test_dot():
    """
    Test the dot product
    """
    i = 1000
    a = random((i, i))
    b = numpy.linalg.inv(a)
    result = numpy.dot(a, b) - numpy.eye(i)

# Test to start. The dict is the value I had with the MKL using EPD 6.0 and without MKL using EPD 5.1
tests = {test_eigenvalue : (752., 3376.),
         test_svd : (4608., 15990.),
         test_inv : (418., 1457.),
         test_det : (186.0, 400.),
         test_dot : (666., 2444.) }

# Setting the following environment variable in the shell executing the script allows
# you limit the maximal number threads used for computation
THREADS_LIMIT_ENV = 'OMP_NUM_THREADS'

def start_benchmark():
    print """Benchmark is made against EPD 6.0,NumPy 1.4 with MKL and EPD 5.1, NumPy 1.3 with ATLAS
on a Thinkpad T60 with Intel CoreDuo 2Ghz CPU on Windows Vista 32 bit
    """
    if os.environ.has_key(THREADS_LIMIT_ENV):
        print "Maximum number of threads used for computation is : %s" % os.environ[THREADS_LIMIT_ENV]
    print ("-" * 80)
    print "Starting timing with numpy %s\nVersion: %s" % (numpy.__version__, sys.version)
    print "%20s : %10s - %5s / %5s" % ("Function", "Timing [ms]", "MKL", "No MKL")
    for fun, bench in tests.items():
        t = timeit.Timer(stmt="%s()" % fun.__name__, setup="from __main__ import %s" % fun.__name__)
        res = t.repeat(repeat=3, number=1)
        timing =  1000.0 * sum(res)/len(res)
        print "%20s : %7.1f ms -  %3.2f / %3.2f" % (fun.__name__, timing, bench[0]/timing, bench[1]/timing)

if __name__ == '__main__':
    start_benchmark()