#!/usr/bin/env python # SPDX-License-Identifier: BSD-2-Clause # # Copyright (c) 2017 embedded brains GmbH & Co. KG # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # 1. Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # 2. 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. # # 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. # import re import libxml2 from libxml2 import xmlNode import matplotlib.pyplot as plt data = open('smpopenmp01.scn').read() data = re.sub(r'\*\*\*.*', '', data) doc = libxml2.parseDoc(data) ctx = doc.xpathNewContext() plt.title('OpenMP Microbench') plt.xlabel('Number of Threads') plt.ylabel('Relative Duration') def m(n): return float(n.getContent()) def p(bench): d = map(m, ctx.xpathEval('/SMPOpenMP01/Microbench/' + bench)) y = [x / d[0] for x in d] x = range(1, len(y) + 1) plt.xticks(x) plt.plot(x, y, label = bench, marker = 'o') p('BarrierBench') p('ParallelBench') p('StaticBench') p('DynamicBench') p('GuidedBench') p('RuntimeBench') p('SingleBench') plt.legend(loc = 'best') plt.show()