#!/usr/bin/env python3 """ 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 (schaller@strw.leidenuniv.nl) (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 . """ import matplotlib matplotlib.use("Agg") import math 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=4.0, type=float, ) parser.add_argument( "--width", dest="width", help="Width of plot in inches (def: 16)", default=16.0, 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": 0.0, "figure.subplot.hspace": 0.0, "lines.markersize": 6, "lines.linewidth": 3.0, } 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=" ", encoding=None) # 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 = math.ceil(len(typesseen) / 4) if not args.nolegend: ax.fill_between([0, 0], nthread, nthread + nrow, facecolor="white") ax.set_ylim(0, nthread + 0.5) ax.legend( loc="lower left", shadow=True, bbox_to_anchor=(0.0, 1.0, 1.0, 0.2), mode="expand", ncol=4, ) 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=0.0) 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))), minor=True) loc = plticker.MultipleLocator(base=expand) ax.yaxis.set_major_locator(loc) ax.grid(True, which="major", axis="y", linestyle="-") pl.savefig(outpng, bbox_inches="tight", dpi=100) print("Graphics done, output written to", outpng) sys.exit(0)