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transpose-numpy.py
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#!/usr/bin/env python3
#
# Copyright (c) 2015, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of Intel Corporation nor the names of its
# contributors may be used to endorse or promote products
# derived from this software without specific prior written
# permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#*******************************************************************
#
# NAME: transpose
#
# PURPOSE: This program measures the time for the transpose of a
# column-major stored matrix into a row-major stored matrix.
#
# USAGE: Program input is the matrix order and the number of times to
# repeat the operation:
#
# transpose <# iterations> <matrix_size>
#
# The output consists of diagnostics to make sure the
# transpose worked and timing statistics.
#
# HISTORY: Written by Rob Van der Wijngaart, February 2009.
# Converted to Python by Jeff Hammond, February 2016.
# *******************************************************************
import sys
print('Python version = ', str(sys.version_info.major)+'.'+str(sys.version_info.minor))
if sys.version_info >= (3, 3):
from time import process_time as timer
else:
from timeit import default_timer as timer
import numpy
print('Numpy version = ', numpy.version.version)
def main():
# ********************************************************************
# read and test input parameters
# ********************************************************************
print('Parallel Research Kernels version ') #, PRKVERSION
print('Python Numpy Matrix transpose: B = A^T')
if len(sys.argv) != 3:
print('argument count = ', len(sys.argv))
sys.exit("Usage: ./transpose <# iterations> <matrix order>")
iterations = int(sys.argv[1])
if iterations < 1:
sys.exit("ERROR: iterations must be >= 1")
order = int(sys.argv[2])
if order < 1:
sys.exit("ERROR: order must be >= 1")
print('Number of iterations = ', iterations)
print('Matrix order = ', order)
# ********************************************************************
# ** Allocate space for the input and transpose matrix
# ********************************************************************
#A = numpy.fromfunction(lambda i,j: i*order+j, (order,order), dtype=float)
A = numpy.arange(order*order,dtype=float).reshape(order,order)
B = numpy.zeros((order,order))
for k in range(0,iterations+1):
if k<1: t0 = timer()
# this actually forms the transpose of A
# B += numpy.transpose(A)
# this only uses the transpose _view_ of A
B += A.T
A += 1.0
t1 = timer()
trans_time = t1 - t0
# ********************************************************************
# ** Analyze and output results.
# ********************************************************************
A = numpy.fromfunction(lambda i,j: ((iterations/2.0)+(order*j+i))*(iterations+1.0), (order,order), dtype=float)
abserr = numpy.linalg.norm(numpy.reshape(B-A,order*order),ord=1)
epsilon=1.e-8
nbytes = 2 * order**2 * 8 # 8 is not sizeof(double) in bytes, but allows for comparison to C etc.
if abserr < epsilon:
print('Solution validates')
avgtime = trans_time/iterations
print('Rate (MB/s): ',1.e-6*nbytes/avgtime, ' Avg time (s): ', avgtime)
else:
print('error ',abserr, ' exceeds threshold ',epsilon)
sys.exit("ERROR: solution did not validate")
if __name__ == '__main__':
main()