comparison 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()