#!/usr/bin/env python3 """ Interactive plot of a task dump. Usage: iplot_tasks.py [options] input.dat where input.dat is a thread info file for a step. Use the '-y interval' flag of the swift or swift_mpi commands to create these (these will need to be built with the --enable-task-debugging configure option). The task plot can be scrolled and zoomed using the standard matplotlib controls, the type of task at a point can be queried by a mouse click (unless the --motion option is in effect when a continuous readout is shown) the task type and tic/toc range are reported in the terminal. Requires the tkinter module. This file is part of SWIFT. Copyright (C) 2019 Peter W. Draper (p.w.draper@durham.ac.uk) All Rights Reserved. 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("TkAgg") import numpy as np import matplotlib.backends.backend_tkagg as tkagg from matplotlib.figure import Figure import tkinter as tk import matplotlib.collections as collections import matplotlib.ticker as plticker import pylab as pl import sys import argparse # import hardcoded data from swift_hardcoded_data import TASKTYPES, SUBTYPES, TASKCOLOURS, SUBCOLOURS # Handle the command line. parser = argparse.ArgumentParser(description="Plot task graphs") parser.add_argument("input", help="Thread data file (-y output)") parser.add_argument( "-m", "--motion", dest="motion", help="Track mouse motion, otherwise clicks (def: clicks)", default=False, action="store_true", ) parser.add_argument( "-l", "--limit", dest="limit", help="Upper time limit in millisecs (def: depends on data)", default=0, type=float, ) 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( "-v", "--verbose", dest="verbose", help="Show colour assignments and other details (def: False)", default=False, action="store_true", ) parser.add_argument( "-r", "--rank", dest="rank", help="The rank to plot, if MPI in effect", default=0, type=int, ) args = parser.parse_args() infile = args.input delta_t = args.limit rank = args.rank # 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": 0.1, "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) # 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]) # Read input. data = pl.loadtxt(infile) # Do we have an MPI file? full_step = data[0, :] if full_step.size == 13: print("# MPI mode") mpimode = True ranks = list(range(int(max(data[:, 0])) + 1)) print("# Number of ranks:", len(ranks)) rankcol = 0 threadscol = 1 taskcol = 2 subtaskcol = 3 ticcol = 5 toccol = 6 else: print("# non MPI mode") mpimode = False rankcol = -1 threadscol = 0 taskcol = 1 subtaskcol = 2 ticcol = 4 toccol = 5 # Get CPU_CLOCK to convert ticks into milliseconds. CPU_CLOCK = float(full_step[-1]) / 1000.0 if args.verbose: print("# CPU frequency:", CPU_CLOCK * 1000.0) nthread = int(max(data[:, threadscol])) + 1 print("# Number of threads:", nthread) # Avoid start and end times of zero. sdata = data[data[:, ticcol] != 0] sdata = sdata[sdata[:, toccol] != 0] # Calculate the data range, if not given. delta_t = delta_t * CPU_CLOCK if delta_t == 0: if mpimode: data = sdata[sdata[:, rankcol] == rank] full_step = data[0, :] tic_step = int(full_step[ticcol]) toc_step = int(full_step[toccol]) 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. if mpimode: data = sdata[sdata[:, rankcol] == rank] full_step = data[0, :] tic_step = int(full_step[ticcol]) toc_step = int(full_step[toccol]) print("# Min tic = ", tic_step) data = data[1:, :] # Exit if no data. if data.size == 0: print("# Rank ", rank, " has no tasks") sys.exit(1) start_t = float(tic_step) data[:, ticcol] -= start_t data[:, toccol] -= start_t end_t = (toc_step - start_t) / CPU_CLOCK tasks = {} tasks[-1] = [] for i in range(nthread): tasks[i] = [] num_lines = pl.shape(data)[0] for line in range(num_lines): thread = int(data[line, threadscol]) tasks[thread].append({}) tasktype = TASKTYPES[int(data[line, taskcol])] subtype = SUBTYPES[int(data[line, subtaskcol])] tasks[thread][-1]["type"] = tasktype tasks[thread][-1]["subtype"] = subtype tic = int(data[line, ticcol]) / CPU_CLOCK toc = int(data[line, toccol]) / CPU_CLOCK tasks[thread][-1]["tic"] = tic tasks[thread][-1]["toc"] = toc if "fof" in tasktype: tasks[thread][-1]["colour"] = TASKCOLOURS[tasktype] elif ( ("self" in tasktype) or ("pair" in tasktype) or ("recv" in tasktype) or ("send" in tasktype) ): fulltype = tasktype + "/" + subtype if fulltype in SUBCOLOURS: tasks[thread][-1]["colour"] = SUBCOLOURS[fulltype] else: tasks[thread][-1]["colour"] = SUBCOLOURS[subtype] else: tasks[thread][-1]["colour"] = TASKCOLOURS[tasktype] # Do the plotting. fig = 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(0.5, nthread + 1.0) ltics = [] ltocs = [] llabels = [] for i in range(nthread): # Collect ranges and colours into arrays. Also indexed lists for lookup tables. tictocs = [] colours = [] tics = [] tocs = [] labels = [] for task in tasks[i]: tictocs.append((task["tic"], task["toc"] - task["tic"])) colours.append(task["colour"]) tics.append(task["tic"]) tocs.append(task["toc"]) labels.append(task["type"] + "/" + task["subtype"]) # Add to look up tables. ltics.append(tics) ltocs.append(tocs) llabels.append(labels) # Now plot. ax.broken_barh(tictocs, [i + 0.55, 0.9], facecolors=colours, linewidth=0) # Start and end of time-step ax.plot([0, 0], [0, nthread + 1], "k--", linewidth=1) ax.plot([end_t, end_t], [0, nthread + 1], "k--", linewidth=1) # Labels. ax.set_xlabel("Wall clock time [ms]") ax.set_ylabel("Thread ID") loc = plticker.MultipleLocator(base=1) ax.yaxis.set_major_locator(loc) ax.grid(True, which="major", axis="y", linestyle="-") class Container: def __init__(self, window, figure, motion, nthread, ltics, ltocs, llabels): self.window = window self.figure = figure self.motion = motion self.nthread = nthread self.ltics = ltics self.ltocs = ltocs self.llabels = llabels def plot(self): canvas = tkagg.FigureCanvasTkAgg(self.figure, master=self.window) wcanvas = canvas.get_tk_widget() wcanvas.config(width=1000, height=300) wcanvas.pack(side=tk.TOP, expand=True, fill=tk.BOTH) toolbar = tkagg.NavigationToolbar2Tk(canvas, self.window) toolbar.update() self.output = tk.StringVar() label = tk.Label( self.window, textvariable=self.output, bg="white", fg="red", bd=2 ) label.pack(side=tk.RIGHT, expand=True, fill=tk.X) wcanvas.pack(side=tk.TOP, expand=True, fill=tk.BOTH) canvas.draw() # Print task type using mouse clicks or motion. if self.motion: fig.canvas.mpl_connect("motion_notify_event", self.onclick) else: fig.canvas.mpl_connect("button_press_event", self.onclick) # Space bar to dump all tasks. Use with caution... fig.canvas.mpl_connect("key_press_event", self.dump) def dump(self, event): # Dump all tasks to the console sorted by tic. xlow = float(event.inaxes.viewLim.x0) xhigh = float(event.inaxes.viewLim.x1) if event.key == " ": dumps = {} for thread in range(nthread): tics = self.ltics[thread] tocs = self.ltocs[thread] labels = self.llabels[thread] for i in range(len(tics)): if (tics[i] > xlow and tics[i] < xhigh) or ( tocs[i] > xlow and tocs[i] < xhigh ): tic = "{0:.3f}".format(tics[i]) toc = "{0:.3f}".format(tocs[i]) dumps[tics[i]] = ( labels[i] + ", tic/toc = " + tic + " / " + toc ) print("") print("Tasks in time range: " + str(xlow) + " -> " + str(xhigh)) for key in sorted(dumps): print(dumps[key]) print("") def onclick(self, event): # Find thread, then scan for bounded task. try: thread = int(round(event.ydata)) - 1 if thread >= 0 and thread < self.nthread: tics = self.ltics[thread] tocs = self.ltocs[thread] labels = self.llabels[thread] for i in range(len(tics)): if event.xdata > tics[i] and event.xdata < tocs[i]: tic = "{0:.3f}".format(tics[i]) toc = "{0:.3f}".format(tocs[i]) outstr = ( "task = " + labels[i] + ", tic/toc = " + tic + " / " + toc ) self.output.set(outstr) break except TypeError: # Ignore out of bounds. pass def quit(self): self.window.destroy() window = tk.Tk() window.protocol("WM_DELETE_WINDOW", window.quit) container = Container(window, fig, args.motion, nthread, ltics, ltocs, llabels) container.plot() window.mainloop()