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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-06 04:26:52 +08:00
Update to benchmarking mode to enable benchmarking with either CPU or GPU solver.
Added benchmarking metric of 'cells per second'.
这个提交包含在：
Craig Warren
@@ -27,7 +27,8 @@ import matplotlib.gridspec as gridspec
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import numpy as np
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from gprMax._version import __version__
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from gprMax.utilities import get_host_info, human_size
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from gprMax.utilities import get_host_info
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from gprMax.utilities import human_size
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"""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."""
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@@ -54,17 +55,18 @@ except KeyError:
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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'])
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print('Host: {}'.format(machineIDlong))
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# Base result - threads and times info from Numpy archive
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# Base result - general info
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print('Model: {}'.format(args.baseresult))
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for i in range(len(baseresult['cputhreads'])):
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print('{} CPU (OpenMP) thread(s): {:g} s'.format(baseresult['cputhreads'][i], baseresult['cputimes'][i]))
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cells = np.array([baseresult['numcells'][0]]) # Length of cubic model side for cells per second metric
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baseplotlabel = os.path.splitext(os.path.split(args.baseresult)[1])[0] + '.in'
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# Base result - arrays for length of cubic model side and cells per second metric
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cells = np.array([baseresult['numcells'][0]])
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cpucellspersec = np.array([(baseresult['numcells'][0] * baseresult['numcells'][1] * baseresult['numcells'][2] * baseresult['iterations']) / baseresult['cputimes'][0]])
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# Base result - CPU threads and times info from Numpy archive
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if baseresult['cputhreads'].size != 0:
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for i in range(len(baseresult['cputhreads'])):
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print('{} CPU (OpenMP) thread(s): {:g} s'.format(baseresult['cputhreads'][i], baseresult['cputimes'][i]))
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cpucellspersec = np.array([(baseresult['numcells'][0] * baseresult['numcells'][1] * baseresult['numcells'][2] * baseresult['iterations']) / baseresult['cputimes'][0]])
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# Base result for GPU if required - time info
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# Base result - GPU time info
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gpuIDs = baseresult['gpuIDs'].tolist()
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if gpuIDs:
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gpucellspersec = np.zeros((len(gpuIDs), 1))
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@@ -79,15 +81,16 @@ if args.otherresults is not None:
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for i, result in enumerate(args.otherresults):
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otherresults.append(dict(np.load(result)))
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print('\nModel: {}'.format(result))
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for thread in range(len(otherresults[i]['cputhreads'])):
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print('{} CPU (OpenMP) thread(s): {:g} s'.format(otherresults[i]['cputhreads'][thread], otherresults[i]['cputimes'][thread]))
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cells = np.append(cells, otherresults[i]['numcells'][0]) # Length of cubic model side for cells per second metric
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otherplotlabels.append(os.path.splitext(os.path.split(result)[1])[0] + '.in')
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# Arrays for length of cubic model side and cells per second metric
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cells = np.append(cells, otherresults[i]['numcells'][0])
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cpucellspersec = np.append(cpucellspersec, (otherresults[i]['numcells'][0] * otherresults[i]['numcells'][1] * otherresults[i]['numcells'][2] * otherresults[i]['iterations']) / otherresults[i]['cputimes'][0])
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# CPU
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if otherresults[i]['cputhreads'].size != 0:
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for thread in range(len(otherresults[i]['cputhreads'])):
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print('{} CPU (OpenMP) thread(s): {:g} s'.format(otherresults[i]['cputhreads'][thread], otherresults[i]['cputimes'][thread]))
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cpucellspersec = np.append(cpucellspersec, (otherresults[i]['numcells'][0] * otherresults[i]['numcells'][1] * otherresults[i]['numcells'][2] * otherresults[i]['iterations']) / otherresults[i]['cputimes'][0])
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# Other results GPU
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# GPU
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othergpuIDs = otherresults[i]['gpuIDs'].tolist()
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if othergpuIDs:
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# Array for cells per second metric
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@@ -113,58 +116,82 @@ markers = ['o', 'd', '^', 's', '*']
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fig, ax = plt.subplots(num=machineID, figsize=(30, 10), facecolor='w', edgecolor='w')
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fig.suptitle(machineIDlong + '\ngprMax v' + version)
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gs = gridspec.GridSpec(1, 3, hspace=0.5)
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plotcount = 0
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###########################################
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# Subplot of CPU (OpenMP) threads vs time #
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###########################################
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ax = plt.subplot(gs[0, 0])
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ax.plot(baseresult['cputhreads'], baseresult['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label=baseplotlabel)
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if baseresult['cputhreads'].size != 0:
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ax = plt.subplot(gs[0, plotcount])
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ax.plot(baseresult['cputhreads'], baseresult['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label=baseplotlabel)
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if args.otherresults is not None:
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for i, result in enumerate(otherresults):
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ax.plot(result['cputhreads'], result['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, ls=next(lines), label=otherplotlabels[i])
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if args.otherresults is not None:
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for i, result in enumerate(otherresults):
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ax.plot(result['cputhreads'], result['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, ls=next(lines), label=otherplotlabels[i])
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ax.set_xlabel('Number of CPU (OpenMP) threads')
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ax.set_ylabel('Time [s]')
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ax.grid()
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legend = ax.legend(loc=1)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
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ax.set_xticks(np.append(baseresult['cputhreads'], 0))
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ax.set_ylim(0, top=ax.get_ylim()[1] * 1.1)
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ax.set_xlabel('Number of CPU (OpenMP) threads')
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ax.set_ylabel('Time [s]')
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ax.grid()
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legend = ax.legend(loc=1)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
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ax.set_xticks(np.append(baseresult['cputhreads'], 0))
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ax.set_ylim(0, top=ax.get_ylim()[1] * 1.1)
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plotcount += 1
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######################################################
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# Subplot of CPU (OpenMP) threads vs speed-up factor #
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######################################################
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colors = itertools.cycle(colorIDs) # Reset color iterator
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ax = plt.subplot(gs[0, 1])
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ax.plot(baseresult['cputhreads'], baseresult['cputimes'][-1] / baseresult['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label=baseplotlabel)
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if baseresult['cputhreads'].size != 0:
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ax = plt.subplot(gs[0, plotcount])
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ax.plot(baseresult['cputhreads'], baseresult['cputimes'][-1] / baseresult['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label=baseplotlabel)
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if args.otherresults is not None:
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for i, result in enumerate(otherresults):
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ax.plot(result['cputhreads'], result['cputimes'][-1] / result['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, ls=next(lines), label=otherplotlabels[i])
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if args.otherresults is not None:
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for i, result in enumerate(otherresults):
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ax.plot(result['cputhreads'], result['cputimes'][-1] / result['cputimes'], color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, ls=next(lines), label=otherplotlabels[i])
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ax.set_xlabel('Number of CPU (OpenMP) threads')
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ax.set_ylabel('Speed-up factor')
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ax.grid()
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legend = ax.legend(loc=2)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
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ax.set_xticks(np.append(baseresult['cputhreads'], 0))
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ax.set_ylim(bottom=1, top=ax.get_ylim()[1] * 1.1)
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ax.set_xlabel('Number of CPU (OpenMP) threads')
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ax.set_ylabel('Speed-up factor')
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ax.grid()
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legend = ax.legend(loc=2)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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ax.set_xlim([0, baseresult['cputhreads'][0] * 1.1])
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ax.set_xticks(np.append(baseresult['cputhreads'], 0))
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ax.set_ylim(bottom=1, top=ax.get_ylim()[1] * 1.1)
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plotcount += 1
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###########################################
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# Subplot of simulation size vs cells/sec #
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###########################################
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def autolabel(rects):
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"""Attach a text label above each bar on a matplotlib bar chart displaying its height.
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Args:
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rects: Handle to bar chart
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"""
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for rect in rects:
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height = rect.get_height()
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ax.text(rect.get_x() + rect.get_width()/2, height,
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'%d' % int(height),
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ha='center', va='bottom', fontsize=10, rotation=90)
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colors = itertools.cycle(colorIDs) # Reset color iterator
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ax = plt.subplot(gs[0, 2])
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ax.plot(cells, cpucellspersec / 1e6, color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label=cpuID)
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ax = plt.subplot(gs[0, plotcount])
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barwidth = 8 # the width of the bars
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if baseresult['cputhreads'].size != 0:
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cpu = ax.bar(cells - (1/2) * barwidth, cpucellspersec / 1e6, barwidth, color=next(colors), edgecolor='none', label=cpuID)
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autolabel(cpu)
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if gpuIDs:
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positions = np.arange(-gpucellspersec.shape[0] / 2, gpucellspersec.shape[0] / 2, 1)
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for i in range(gpucellspersec.shape[0]):
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ax.plot(cells, gpucellspersec[i,:] / 1e6, color=next(colors), marker=markers[0], markeredgecolor='none', ms=8, lw=2, label='NVIDIA ' + gpuIDs[i])
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gpu = ax.bar(cells + positions[i] * barwidth, gpucellspersec[i,:] / 1e6, barwidth, color=next(colors), edgecolor='none', label='NVIDIA ' + gpuIDs[i])
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autolabel(gpu)
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ax.set_xlabel('Side length of cubic domain [cells]')
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ax.set_ylabel('Performance [Mcells/s]')
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@@ -172,6 +199,8 @@ ax.grid()
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legend = ax.legend(loc=2)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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ax.set_xticks(cells)
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ax.set_xticklabels(cells)
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ax.set_xlim([0, cells[-1] * 1.1])
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ax.set_ylim(bottom=0, top=ax.get_ylim()[1] * 1.1)
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