你已经派生过 gprMax
镜像自地址
https://gitee.com/sunhf/gprMax.git
已同步 2025-08-06 12:36:51 +08:00
Plotting updated in line with benchmarking overhaul.
这个提交包含在：
Craig Warren
@@ -1,51 +1,101 @@
|
||||
# Copyright (C) 2015-2017: The University of Edinburgh
|
||||
# Authors: Craig Warren and Antonis Giannopoulos
|
||||
#
|
||||
# This file is part of gprMax.
|
||||
#
|
||||
# gprMax is free software: you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation, either version 3 of the License, or
|
||||
# (at your option) any later version.
|
||||
#
|
||||
# gprMax is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License
|
||||
# along with gprMax. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import sys
|
||||
|
||||
import numpy as np
|
||||
import h5py
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.gridspec as gridspec
|
||||
import numpy as np
|
||||
|
||||
from gprMax._version import __version__
|
||||
from gprMax.utilities import get_host_info
|
||||
from gprMax.utilities import get_host_info, human_size
|
||||
|
||||
"""Plots execution times and speedup factors from benchmarking models run with different numbers of threads. Results are read from a NumPy archive."""
|
||||
|
||||
"""Plots execution times and speedup factors from benchmarking models run with different numbers of CPU (OpenMP) threads. Can also benchmark GPU(s) if required. Results are read from a NumPy archive."""
|
||||
|
||||
# Parse command line arguments
|
||||
parser = argparse.ArgumentParser(description='Plots execution times and speedup factors from benchmarking models run with different numbers of threads. Results are read from a NumPy archive.', usage='cd gprMax; python -m tests.benchmarking.plot_benchmark numpyfile')
|
||||
parser = argparse.ArgumentParser(description='Plots execution times and speedup factors from benchmarking models run with different numbers of CPU (OpenMP) threads. Can also benchmark GPU(s) if required. Results are read from a NumPy archive.', usage='cd gprMax; python -m tests.benchmarking.plot_benchmark numpyfile')
|
||||
parser.add_argument('baseresult', help='name of NumPy archive file including path')
|
||||
parser.add_argument('--otherresults', default=None, help='list of NumPy archives file including path', nargs='+')
|
||||
args = parser.parse_args()
|
||||
|
||||
# Load base result
|
||||
baseresult = np.load(args.baseresult)
|
||||
baseresult = dict(np.load(args.baseresult))
|
||||
|
||||
# Get machine/CPU/OS details
|
||||
hostinfo = get_host_info()
|
||||
try:
|
||||
machineIDlong = str(baseresult['machineID'])
|
||||
# machineIDlong = 'Dell PowerEdge R630; Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40GHz; Linux (3.10.0-327.18.2.el7.x86_64)' # Use to manually describe machine
|
||||
machineID = machineIDlong.split(';')[0]
|
||||
cpuID = machineIDlong.split(';')[1]
|
||||
cpuID = cpuID.split('GHz')[0].split('x')[1][1::] + 'GHz'
|
||||
except KeyError:
|
||||
hostinfo = get_host_info()
|
||||
machineIDlong = '; '.join([hostinfo['machineID'], hostinfo['cpuID'], hostinfo['osversion']])
|
||||
print('MachineID: {}'.format(machineIDlong))
|
||||
hyperthreading = ', {} cores with Hyper-Threading'.format(hostinfo['logicalcores']) if hostinfo['hyperthreading'] else ''
|
||||
machineIDlong = '{}; {} x {} ({} cores{}); {} RAM; {}'.format(hostinfo['machineID'], hostinfo['sockets'], hostinfo['cpuID'], hostinfo['physicalcores'], hyperthreading, human_size(hostinfo['ram'], a_kilobyte_is_1024_bytes=True), hostinfo['osversion'])
|
||||
print('Host: {}'.format(machineIDlong))
|
||||
|
||||
# Base result info
|
||||
# Base result - threads and times info from Numpy archive
|
||||
print('Model: {}'.format(args.baseresult))
|
||||
for thread in range(len(baseresult['threads'])):
|
||||
print('{} thread(s): {:g} s'.format(baseresult['threads'][thread], baseresult['benchtimes'][thread]))
|
||||
for i in range(len(baseresult['cputhreads'])):
|
||||
print('{} CPU (OpenMP) thread(s): {:g} s'.format(baseresult['cputhreads'][i], baseresult['cputimes'][i]))
|
||||
baseplotlabel = os.path.splitext(os.path.split(args.baseresult)[1])[0] + '.in'
|
||||
|
||||
# Load other results and info
|
||||
# Base result - arrays for length of cubic model side and cells per second metric
|
||||
cells = np.array([baseresult['numcells'][0]])
|
||||
cpucellspersec = np.array([(baseresult['numcells'][0] * baseresult['numcells'][1] * baseresult['numcells'][2] * baseresult['iterations']) / baseresult['cputimes'][0]])
|
||||
|
||||
# Base result for GPU if required - time info
|
||||
gpuIDs = baseresult['gpuIDs'].tolist()
|
||||
if gpuIDs:
|
||||
gpucellspersec = np.zeros((len(gpuIDs), 1))
|
||||
for i in range(len(gpuIDs)):
|
||||
print('NVIDIA {}: {:g} s'.format(gpuIDs[i], baseresult['gputimes'][i]))
|
||||
gpucellspersec[i] = (baseresult['numcells'][0] * baseresult['numcells'][1] * baseresult['numcells'][2] * baseresult['iterations']) / baseresult['gputimes'][i]
|
||||
|
||||
# Load any other results and info
|
||||
otherresults = []
|
||||
otherplotlabels = []
|
||||
if args.otherresults is not None:
|
||||
for i, result in enumerate(args.otherresults):
|
||||
otherresults.append(np.load(result))
|
||||
print('Model: {}'.format(result))
|
||||
for thread in range(len(otherresults[i]['threads'])):
|
||||
print('{} thread(s): {:g} s'.format(otherresults[i]['threads'][thread], otherresults[i]['benchtimes'][thread]))
|
||||
otherresults.append(dict(np.load(result)))
|
||||
print('\nModel: {}'.format(result))
|
||||
for thread in range(len(otherresults[i]['cputhreads'])):
|
||||
print('{} CPU (OpenMP) thread(s): {:g} s'.format(otherresults[i]['cputhreads'][thread], otherresults[i]['cputimes'][thread]))
|
||||
otherplotlabels.append(os.path.splitext(os.path.split(result)[1])[0] + '.in')
|
||||
|
||||
# Arrays for length of cubic model side and cells per second metric
|
||||
cells = np.append(cells, otherresults[i]['numcells'][0])
|
||||
cpucellspersec = np.append(cpucellspersec, (otherresults[i]['numcells'][0] * otherresults[i]['numcells'][1] * otherresults[i]['numcells'][2] * otherresults[i]['iterations']) / otherresults[i]['cputimes'][0])
|
||||
|
||||
# Other results GPU
|
||||
othergpuIDs = otherresults[i]['gpuIDs'].tolist()
|
||||
if othergpuIDs:
|
||||
# Array for cells per second metric
|
||||
tmp = np.zeros((len(gpuIDs), len(args.otherresults) + 1))
|
||||
tmp[:gpucellspersec.shape[0],:gpucellspersec.shape[1]] = gpucellspersec
|
||||
gpucellspersec = tmp
|
||||
for j in range(len(othergpuIDs)):
|
||||
print('NVIDIA {}: {:g} s'.format(othergpuIDs[j], otherresults[i]['gputimes'][j]))
|
||||
gpucellspersec[j,i+1] = (otherresults[i]['numcells'][0] * otherresults[i]['numcells'][1] * otherresults[i]['numcells'][2] * otherresults[i]['iterations']) / otherresults[i]['gputimes'][j]
|
||||
|
||||
# Get gprMax version
|
||||
try:
|
||||
@@ -53,62 +103,77 @@ try:
|
||||
except KeyError:
|
||||
version = __version__
|
||||
|
||||
# Plot colours from http://tools.medialab.sciences-po.fr/iwanthue/index.php
|
||||
colors = ['#5CB7C6', '#E60D30', '#A21797', '#A3B347']
|
||||
# Create/setup plot figure
|
||||
colors = ['#E60D30', '#5CB7C6', '#A21797', '#A3B347'] # Plot colours from http://tools.medialab.sciences-po.fr/iwanthue/index.php
|
||||
lines = ['--', ':', '-.']
|
||||
fig, ax = plt.subplots(num=machineID, figsize=(30, 10), facecolor='w', edgecolor='w')
|
||||
fig.suptitle(machineIDlong + '\ngprMax v' + version)
|
||||
gs = gridspec.GridSpec(1, 3, hspace=0.5)
|
||||
|
||||
fig, ax = plt.subplots(num=machineIDlong, figsize=(20, 10), facecolor='w', edgecolor='w')
|
||||
fig.suptitle(machineIDlong)
|
||||
gs = gridspec.GridSpec(1, 2, hspace=0.5)
|
||||
###########################################
|
||||
# Subplot of CPU (OpenMP) threads vs time #
|
||||
###########################################
|
||||
ax = plt.subplot(gs[0, 0])
|
||||
ax.plot(baseresult['threads'], baseresult['benchtimes'], color=colors[1], marker='.', ms=10, lw=2, label=baseplotlabel + ' (v' + version + ')')
|
||||
ax.plot(baseresult['cputhreads'], baseresult['cputimes'], color=colors[0], marker='.', ms=10, lw=2, label=baseplotlabel)
|
||||
|
||||
if args.otherresults is not None:
|
||||
for i, result in enumerate(otherresults):
|
||||
ax.plot(result['threads'], result['benchtimes'], color=colors[1], marker='.', ms=10, lw=2, ls=lines[i], label=otherplotlabels[i] + ' (v' + version + ')')
|
||||
ax.plot(result['cputhreads'], result['cputimes'], color=colors[0], marker='.', ms=10, lw=2, ls=lines[i], label=otherplotlabels[i])
|
||||
|
||||
# ax.plot(results['threads'], results['bench1'], color=colors[1], marker='.', ms=10, lw=2, label='bench_100x100x100.in (v3.0.0b21)')
|
||||
# ax.plot(results['threads'], results['bench1c'], color=colors[0], marker='.', ms=10, lw=2, label='bench_100x100x100.in (v2)')
|
||||
# ax.plot(results['threads'], results['bench2'], color=colors[1], marker='.', ms=10, lw=2, ls='--', label='bench_150x150x150.in (v3.0.0b21)')
|
||||
# ax.plot(results['threads'], results['bench2c'], color=colors[0], marker='.', ms=10, lw=2, ls='--', label='bench_150x150x150.in (v2)')
|
||||
|
||||
ax.set_xlabel('Number of threads')
|
||||
ax.set_xlabel('Number of CPU (OpenMP) threads')
|
||||
ax.set_ylabel('Time [s]')
|
||||
ax.grid()
|
||||
|
||||
legend = ax.legend(loc=1)
|
||||
frame = legend.get_frame()
|
||||
frame.set_edgecolor('white')
|
||||
|
||||
ax.set_xlim([0, baseresult['threads'][0] * 1.1])
|
||||
ax.set_xticks(np.append(baseresult['threads'], 0))
|
||||
ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
|
||||
ax.set_xticks(np.append(baseresult['cputhreads'], 0))
|
||||
ax.set_ylim(0, top=ax.get_ylim()[1] * 1.1)
|
||||
|
||||
######################################################
|
||||
# Subplot of CPU (OpenMP) threads vs speed-up factor #
|
||||
######################################################
|
||||
ax = plt.subplot(gs[0, 1])
|
||||
ax.plot(baseresult['threads'], baseresult['benchtimes'][-1] / baseresult['benchtimes'], color=colors[1], marker='.', ms=10, lw=2, label=baseplotlabel + ' (v' + version + ')')
|
||||
ax.plot(baseresult['cputhreads'], baseresult['cputimes'][-1] / baseresult['cputimes'], color=colors[0], marker='.', ms=10, lw=2, label=baseplotlabel)
|
||||
|
||||
if args.otherresults is not None:
|
||||
for i, result in enumerate(otherresults):
|
||||
ax.plot(result['threads'], result['benchtimes'][-1] / result['benchtimes'], color=colors[1], marker='.', ms=10, lw=2, ls=lines[i], label=otherplotlabels[i] + ' (v' + version + ')')
|
||||
ax.plot(result['cputhreads'], result['cputimes'][-1] / result['cputimes'], color=colors[0], marker='.', ms=10, lw=2, ls=lines[i], label=otherplotlabels[i])
|
||||
|
||||
# ax.plot(results['threads'], results['bench1'][0] / results['bench1'], color=colors[1], marker='.', ms=10, lw=2, label='bench_100x100x100.in (v3.0.0b21)')
|
||||
# ax.plot(results['threads'], results['bench1c'][1] / results['bench1c'], color=colors[0], marker='.', ms=10, lw=2, label='bench_100x100x100.in (v2)')
|
||||
# ax.plot(results['threads'], results['bench2'][0] / results['bench2'], color=colors[1], marker='.', ms=10, lw=2, ls='--', label='bench_150x150x150.in (v3.0.0b21)')
|
||||
# ax.plot(results['threads'], results['bench2c'][1] / results['bench2c'], color=colors[0], marker='.', ms=10, lw=2, ls='--', label='bench_150x150x150.in (v2)')
|
||||
|
||||
ax.set_xlabel('Number of threads')
|
||||
ax.set_xlabel('Number of CPU (OpenMP) threads')
|
||||
ax.set_ylabel('Speed-up factor')
|
||||
ax.grid()
|
||||
|
||||
legend = ax.legend(loc=1)
|
||||
legend = ax.legend(loc=2)
|
||||
frame = legend.get_frame()
|
||||
frame.set_edgecolor('white')
|
||||
|
||||
ax.set_xlim([0, baseresult['threads'][0] * 1.1])
|
||||
ax.set_xticks(np.append(baseresult['threads'], 0))
|
||||
ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
|
||||
ax.set_xticks(np.append(baseresult['cputhreads'], 0))
|
||||
ax.set_ylim(bottom=1, top=ax.get_ylim()[1] * 1.1)
|
||||
|
||||
# Save a pdf of the plot
|
||||
###########################################
|
||||
# Subplot of simulation size vs cells/sec #
|
||||
###########################################
|
||||
ax = plt.subplot(gs[0, 2])
|
||||
cells = np.array([100, 150, 200, 300])
|
||||
ax.plot(cells, cpucellspersec / 1e6, color=colors[0], marker='.', ms=10, lw=2, label=cpuID)
|
||||
|
||||
if gpuIDs:
|
||||
for i in range(gpucellspersec.shape[0]):
|
||||
ax.plot(cells, gpucellspersec[i,:] / 1e6, color=colors[i+1], marker='.', ms=10, lw=2, label='NVIDIA ' + gpuIDs[i])
|
||||
|
||||
ax.set_xlabel('Side length of cubic domain [cells]')
|
||||
ax.set_ylabel('Performance [Mcells/s]')
|
||||
ax.grid()
|
||||
legend = ax.legend(loc=2)
|
||||
frame = legend.get_frame()
|
||||
frame.set_edgecolor('white')
|
||||
ax.set_xlim([0, cells[-1] * 1.1])
|
||||
ax.set_ylim(bottom=0, top=ax.get_ylim()[1] * 1.1)
|
||||
|
||||
##########################
|
||||
# Save a png of the plot #
|
||||
##########################
|
||||
fig.savefig(os.path.join(os.path.dirname(args.baseresult), machineID.replace(' ', '_') + '.png'), dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)
|
||||
#fig.savefig(os.path.join(os.path.dirname(args.baseresult), machineID.replace(' ', '_') + '.pdf'), dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
|
||||
|
||||
plt.show()
|
||||
|
||||
在新工单中引用
屏蔽一个用户