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Matthieu Schaller authoredMatthieu Schaller authored
plot_threadpool.py 9.23 KiB
#!/usr/bin/env python
"""
Usage:
plot_threadpool.py [options] input.dat output.png
where input.dat is a threadpool info file for a step. Use the '-Y interval'
flag of the swift command to create these. The output plot will be called
'output.png'. The --limit option can be used to produce plots with the same
time span and the --expand option to expand each thread line into '*expand'
lines, so that adjacent tasks of the same type can be distinguished. Other
options can be seen using the --help flag.
This file is part of SWIFT.
Copyright (c) 2015 Pedro Gonnet (pedro.gonnet@durham.ac.uk),
Bert Vandenbroucke (bert.vandenbroucke@ugent.be)
Matthieu Schaller (matthieu.schaller@durham.ac.uk)
(c) 2017 Peter W. Draper (p.w.draper@durham.ac.uk)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program 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 Lesser General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
import matplotlib
matplotlib.use("Agg")
import matplotlib.collections as collections
import matplotlib.ticker as plticker
import pylab as pl
import sys
import argparse
# Handle the command line.
parser = argparse.ArgumentParser(description="Plot threadpool function graphs")
parser.add_argument("input", help="Threadpool data file (-Y output)")
parser.add_argument("outpng", help="Name for output graphic file (PNG)")
parser.add_argument("-l", "--limit", dest="limit",
help="Upper time limit in millisecs (def: depends on data)",
default=0, type=float)
parser.add_argument("-e", "--expand", dest="expand",
help="Thread expansion factor (def: 1)",
default=1, type=int)
parser.add_argument("--height", dest="height",
help="Height of plot in inches (def: 4)",
default=4., type=float)
parser.add_argument("--width", dest="width",
help="Width of plot in inches (def: 16)",
default=16., type=float)
parser.add_argument("--nolegend", dest="nolegend",
help="Whether to show the legend (def: False)",
default=False, action="store_true")
parser.add_argument("-v", "--verbose", dest="verbose",
help="Show colour assignments and other details (def: False)",
default=False, action="store_true")
parser.add_argument("-m", "--mintic", dest="mintic",
help="Value of the smallest tic (def: least in input file)",
default=-1, type=int)
args = parser.parse_args()
infile = args.input
outpng = args.outpng
delta_t = args.limit
expand = args.expand
mintic = args.mintic
# Basic plot configuration.
PLOT_PARAMS = {"axes.labelsize": 10,
"axes.titlesize": 10,
"font.size": 12,
"legend.fontsize": 12,
"xtick.labelsize": 10,
"ytick.labelsize": 10,
"figure.figsize" : (args.width, args.height),
"figure.subplot.left" : 0.03,
"figure.subplot.right" : 0.995,
"figure.subplot.bottom" : 0.09,
"figure.subplot.top" : 0.99,
"figure.subplot.wspace" : 0.,
"figure.subplot.hspace" : 0.,
"lines.markersize" : 6,
"lines.linewidth" : 3.
}
pl.rcParams.update(PLOT_PARAMS)
# A number of colours for the various types. Recycled when there are
# more task types than colours...
colours = ["cyan", "lightgray", "darkblue", "yellow", "tan", "dodgerblue",
"sienna", "aquamarine", "bisque", "blue", "green", "lightgreen",
"brown", "purple", "moccasin", "olivedrab", "chartreuse",
"olive", "darkgreen", "green", "mediumseagreen",
"mediumaquamarine", "darkslategrey", "mediumturquoise",
"black", "cadetblue", "skyblue", "red", "slategray", "gold",
"slateblue", "blueviolet", "mediumorchid", "firebrick",
"magenta", "hotpink", "pink", "orange", "lightgreen"]
maxcolours = len(colours)
# Read header. First two lines.
with open(infile) as infid:
head = [next(infid) for x in range(2)]
header = head[1][2:].strip()
header = eval(header)
nthread = int(header['num_threads']) + 1
CPU_CLOCK = float(header['cpufreq']) / 1000.0
print("Number of threads: ", nthread)
if args.verbose:
print("CPU frequency:", CPU_CLOCK * 1000.0)
# Read input.
data = pl.genfromtxt(infile, dtype=None, delimiter=" ")
# Mixed types, so need to separate.
tics = []
tocs = []
funcs = []
threads = []
chunks = []
for i in data:
if i[0] != "#":
funcs.append(i[0].replace("_mapper", ""))
if i[1] < 0:
threads.append(nthread-1)
else:
threads.append(i[1])
chunks.append(i[2])
tics.append(i[3])
tocs.append(i[4])
tics = pl.array(tics)
tocs = pl.array(tocs)
funcs = pl.array(funcs)
threads = pl.array(threads)
chunks = pl.array(chunks)
# Recover the start and end time
mintic_step = min(tics)
tic_step = mintic_step
toc_step = max(tocs)
print("# Min tic = ", mintic_step)
if mintic > 0:
tic_step = mintic
# Calculate the time range, if not given.
delta_t = delta_t * CPU_CLOCK
if delta_t == 0:
dt = toc_step - tic_step
if dt > delta_t:
delta_t = dt
print("Data range: ", delta_t / CPU_CLOCK, "ms")
# Once more doing the real gather and plots this time.
start_t = float(tic_step)
tics -= tic_step
tocs -= tic_step
end_t = (toc_step - start_t) / CPU_CLOCK
# Get all "task" names and assign colours.
TASKTYPES = pl.unique(funcs)
print(TASKTYPES)
# Set colours of task/subtype.
TASKCOLOURS = {}
ncolours = 0
for task in TASKTYPES:
TASKCOLOURS[task] = colours[ncolours]
ncolours = (ncolours + 1) % maxcolours
# For fiddling with colours...
if args.verbose:
print("#Selected colours:")
for task in sorted(TASKCOLOURS.keys()):
print("# " + task + ": " + TASKCOLOURS[task])
for task in sorted(SUBCOLOURS.keys()):
print("# " + task + ": " + SUBCOLOURS[task])
tasks = {}
tasks[-1] = []
for i in range(nthread*expand):
tasks[i] = []
# Counters for each thread when expanding.
ecounter = []
for i in range(nthread):
ecounter.append(0)
for i in range(len(threads)):
thread = threads[i]
# Expand to cover extra lines if expanding.
ethread = thread * expand + (ecounter[thread] % expand)
ecounter[thread] = ecounter[thread] + 1
thread = ethread
tasks[thread].append({})
tasks[thread][-1]["type"] = funcs[i]
tic = tics[i] / CPU_CLOCK
toc = tocs[i] / CPU_CLOCK
tasks[thread][-1]["tic"] = tic
tasks[thread][-1]["toc"] = toc
tasks[thread][-1]["colour"] = TASKCOLOURS[funcs[i]]
# Use expanded threads from now on.
nthread = nthread * expand
typesseen = []
fig = pl.figure()
ax = fig.add_subplot(1,1,1)
ax.set_xlim(-delta_t * 0.01 / CPU_CLOCK, delta_t * 1.01 / CPU_CLOCK)
ax.set_ylim(0, nthread)
# Fake thread is used to colour the whole range, do that first.
tictocs = []
colours = []
j = 0
for task in tasks[nthread - expand]:
tictocs.append((task["tic"], task["toc"] - task["tic"]))
colours.append(task["colour"])
ax.broken_barh(tictocs, [0,(nthread-1)], facecolors = colours, linewidth=0, alpha=0.15)
# And we don't plot the fake thread.
nthread = nthread - expand
for i in range(nthread):
# Collect ranges and colours into arrays.
tictocs = []
colours = []
j = 0
for task in tasks[i]:
tictocs.append((task["tic"], task["toc"] - task["tic"]))
colours.append(task["colour"])
# Legend support, collections don't add to this.
qtask = task["type"]
if qtask not in typesseen:
pl.plot([], [], color=task["colour"], label=qtask)
typesseen.append(qtask)
# Now plot.
ax.broken_barh(tictocs, [i+0.05,0.90], facecolors = colours, linewidth=0)
# Legend and room for it.
nrow = len(typesseen) / 5
if not args.nolegend:
ax.fill_between([0, 0], nthread+0.5, nthread + nrow + 0.5, facecolor="white")
ax.set_ylim(0, nthread + 0.5)
ax.legend(loc=1, shadow=True, bbox_to_anchor=(0., 1.05 ,1., 0.2), mode="expand", ncol=5)
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width, box.height*0.8])
# Start and end of time-step
real_start_t = (mintic_step - tic_step)/ CPU_CLOCK
ax.plot([real_start_t, real_start_t], [0, nthread + nrow + 1], 'k--', linewidth=1)
ax.plot([end_t, end_t], [0, nthread + nrow + 1], 'k--', linewidth=1)
ax.set_xlabel("Wall clock time [ms]", labelpad=0.)
if expand == 1:
ax.set_ylabel("Thread ID", labelpad=0 )
else:
ax.set_ylabel("Thread ID * " + str(expand), labelpad=0 )
ax.set_yticks(pl.array(list(range(nthread))), True)
loc = plticker.MultipleLocator(base=expand)
ax.yaxis.set_major_locator(loc)
ax.grid(True, which='major', axis="y", linestyle="-")
pl.show()
pl.savefig(outpng)
print("Graphics done, output written to", outpng)
sys.exit(0)