Add new scripts to output basic analysis of the task dumps

examples/analyse_tasks.py

+#!/usr/bin/env python
+"""
+Usage:
+    analsyse_tasks.py [options] input.dat
+
+where input.dat is a thread info file for a step.  Use the '-y interval' flag
+of the swift command to create these.
+
+The output is an analysis of the task timings, including deadtime per thread
+and step, total amount of time spent for each task type, for the whole step
+and per thread and the minimum and maximum times spent per task type.
+
+This file is part of SWIFT.
+Copyright (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="Analyse task dumps")
+
+parser.add_argument("input", help="Thread data file (-y output)")
+parser.add_argument("-v", "--verbose", dest="verbose",
+                    help="Verbose output (default: False)",
+                    default=False, action="store_true")
+
+args = parser.parse_args()
+infile = args.input
+
+#  Tasks and subtypes. Indexed as in tasks.h.
+TASKTYPES = ["none", "sort", "self", "pair", "sub_self", "sub_pair",
+             "init_grav", "ghost", "extra_ghost", "drift_part",
+             "drift_gpart", "kick1", "kick2", "timestep", "send", "recv",
+             "grav_top_level", "grav_long_range", "grav_mm", "grav_down",
+             "cooling", "sourceterms", "count"]
+
+SUBTYPES = ["none", "density", "gradient", "force", "grav", "external_grav",
+            "tend", "xv", "rho", "gpart", "multipole", "spart", "count"]
+
+#  Read input.
+data = pl.loadtxt( infile )
+
+nthread = int(max(data[:,0])) + 1
+print "Number of threads:", nthread
+
+#  Recover the start and end time
+full_step = data[0,:]
+tic_step = int(full_step[4])
+toc_step = int(full_step[5])
+CPU_CLOCK = float(full_step[-1]) / 1000.0
+data = data[1:,:]
+if args.verbose:
+    print "CPU frequency:", CPU_CLOCK * 1000.0
+
+#  Avoid start and end times of zero.
+data = data[data[:,4] != 0]
+data = data[data[:,5] != 0]
+
+#  Calculate the time range.
+total_t = (toc_step - tic_step)/ CPU_CLOCK
+print "Data range: ", total_t, "ms"
+
+#  Correct times to relative values.
+start_t = float(tic_step)
+data[:,4] -= start_t
+data[:,5] -= start_t
+
+tasks = {}
+tasks[-1] = []
+for i in range(nthread):
+    tasks[i] = []
+
+#  Gather into by thread data.
+num_lines = pl.size(data) / 10
+for line in range(num_lines):
+    thread = int(data[line,0])
+    tic = int(data[line,4]) / CPU_CLOCK
+    toc = int(data[line,5]) / CPU_CLOCK
+    tasktype = int(data[line,1])
+    subtype = int(data[line,2])
+
+    tasks[thread].append([tic,toc,tasktype,subtype])
+
+#  Sort by tic.
+for i in range(nthread):
+    tasks[i] = sorted(tasks[i], key=lambda task: task[0])
+
+#  Times per task.
+print "# Task times:"
+print "# {0:<16s}: {1:>7s} {2:>9s} {3:>9s} {4:>9s} {5:>9s} {6:>9s}"\
+      .format("type/subtype", "count","minimum", "maximum",
+              "sum", "mean", "percent")
+alltasktimes = {}
+for i in range(nthread):
+    tasktimes = {}
+    for task in tasks[i]:
+        key = TASKTYPES[task[2]] + "/" + SUBTYPES[task[3]]
+        dt = task[1] - task[0]
+        if not key in tasktimes:
+            tasktimes[key] = []
+        tasktimes[key].append(dt)
+
+        if not key in alltasktimes:
+            alltasktimes[key] = []
+        alltasktimes[key].append(dt)
+
+    print "# Thread : ", i
+    for key in sorted(tasktimes.keys()):
+        taskmin = min(tasktimes[key])
+        taskmax = max(tasktimes[key])
+        tasksum = sum(tasktimes[key])
+        print "{0:18s}: {1:7d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+              .format(key, len(tasktimes[key]), taskmin, taskmax, tasksum,
+                      tasksum / len(tasktimes[key]), tasksum / total_t * 100.0)
+    print
+
+print "# All threads : "
+for key in sorted(alltasktimes.keys()):
+    taskmin = min(alltasktimes[key])
+    taskmax = max(alltasktimes[key])
+    tasksum = sum(alltasktimes[key])
+    print "{0:18s}: {1:7d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+          .format(key, len(alltasktimes[key]), taskmin, taskmax, tasksum,
+                  tasksum / len(alltasktimes[key]),
+                  tasksum / (nthread * total_t) * 100.0)
+print
+
+#  Dead times.
+print "# Deadtimes:"
+print "# no.    : {0:>9s} {1:>9s} {2:>9s} {3:>9s} {4:>9s} {5:>9s}"\
+      .format("count", "minimum", "maximum", "sum", "mean", "percent")
+alldeadtimes = []
+for i in range(nthread):
+    deadtimes = []
+    last = 0
+    for task in tasks[i]:
+        dt = task[0] - last
+        deadtimes.append(dt)
+        last = task[1]
+    dt = total_t - last
+    deadtimes.append(dt)
+
+    deadmin = min(deadtimes)
+    deadmax = max(deadtimes)
+    deadsum = sum(deadtimes)
+    print "thread {0:2d}: {1:9d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+          .format(i, len(deadtimes), deadmin, deadmax, deadsum,
+                  deadsum / len(deadtimes), deadsum / total_t * 100.0)
+    alldeadtimes.extend(deadtimes)
+
+deadmin = min(alldeadtimes)
+deadmax = max(alldeadtimes)
+deadsum = sum(alldeadtimes)
+print "all      : {0:9d} {1:9.4f} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.2f}"\
+      .format(len(alldeadtimes), deadmin, deadmax, deadsum,
+              deadsum / len(alldeadtimes),
+              deadsum / (nthread * total_t ) * 100.0)
+print
+
+
+sys.exit(0)

examples/analyse_tasks_MPI.py

+#!/usr/bin/env python
+"""
+Usage:
+    analsyse_tasks_MPI.py [options] input.dat
+
+where input.dat is a thread info file for an MPI step.  Use the '-y interval'
+flag of the swift command to create these.
+
+The output is an analysis of the task timings, including deadtime per thread
+and step, total amount of time spent for each task type, for the whole step
+and per thread and the minimum and maximum times spent per task type.
+
+This file is part of SWIFT.
+Copyright (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="Analyse task dumps")
+
+parser.add_argument("input", help="Thread data file (-y output)")
+parser.add_argument("-v", "--verbose", dest="verbose",
+                    help="Verbose output (default: False)",
+                    default=False, action="store_true")
+
+args = parser.parse_args()
+infile = args.input
+
+#  Tasks and subtypes. Indexed as in tasks.h.
+TASKTYPES = ["none", "sort", "self", "pair", "sub_self", "sub_pair",
+             "init_grav", "ghost", "extra_ghost", "drift_part",
+             "drift_gpart", "kick1", "kick2", "timestep", "send", "recv",
+             "grav_top_level", "grav_long_range", "grav_mm", "grav_down",
+             "cooling", "sourceterms", "count"]
+
+SUBTYPES = ["none", "density", "gradient", "force", "grav", "external_grav",
+            "tend", "xv", "rho", "gpart", "multipole", "spart", "count"]
+
+#  Read input.
+data = pl.loadtxt( infile )
+
+#  Get the CPU clock to convert ticks into milliseconds.
+full_step = data[0,:]
+CPU_CLOCK = float(full_step[-1]) / 1000.0
+if args.verbose:
+    print "# CPU frequency:", CPU_CLOCK * 1000.0
+
+nranks = int(max(data[:,0])) + 1
+print "# Number of ranks:", nranks
+nthread = int(max(data[:,1])) + 1
+print "# Number of threads:", nthread
+
+#  Avoid start and end times of zero.
+sdata = data[data[:,5] != 0]
+sdata = data[data[:,6] != 0]
+
+#  Now we process all the ranks.
+for rank in range(nranks):
+    print "# Rank", rank
+    data = sdata[sdata[:,0] == rank]
+
+    #  Recover the start and end time
+    full_step = data[0,:]
+    tic_step = int(full_step[5])
+    toc_step = int(full_step[6])
+    data = data[1:,:]
+
+    #  Avoid start and end times of zero.
+    data = data[data[:,5] != 0]
+    data = data[data[:,6] != 0]
+
+    #  Calculate the time range.
+    total_t = (toc_step - tic_step)/ CPU_CLOCK
+    print "# Data range: ", total_t, "ms"
+
+    #  Correct times to relative values.
+    start_t = float(tic_step)
+    data[:,5] -= start_t
+    data[:,6] -= start_t
+    end_t = (toc_step - start_t) / CPU_CLOCK
+
+    tasks = {}
+    tasks[-1] = []
+    for i in range(nthread):
+        tasks[i] = []
+
+    #  Gather into by thread data.
+    num_lines = pl.size(data) / 12
+    for line in range(num_lines):
+        thread = int(data[line,1])
+        tic = int(data[line,5]) / CPU_CLOCK
+        toc = int(data[line,6]) / CPU_CLOCK
+        tasktype = int(data[line,2])
+        subtype = int(data[line,3])
+
+        tasks[thread].append([tic,toc,tasktype,subtype])
+
+    #  Sort by tic.
+    for i in range(nthread):
+        tasks[i] = sorted(tasks[i], key=lambda task: task[0])
+
+    #  Times per task.
+    print "# Task times:"
+    print "# {0:<16s}: {1:>7s} {2:>9s} {3:>9s} {4:>9s} {5:>9s} {6:>9s}"\
+          .format("type/subtype", "count","minimum", "maximum",
+                  "sum", "mean", "percent")
+    alltasktimes = {}
+    for i in range(nthread):
+        tasktimes = {}
+        for task in tasks[i]:
+            key = TASKTYPES[task[2]] + "/" + SUBTYPES[task[3]]
+            dt = task[1] - task[0]
+            if not key in tasktimes:
+                tasktimes[key] = []
+            tasktimes[key].append(dt)
+
+            if not key in alltasktimes:
+                alltasktimes[key] = []
+            alltasktimes[key].append(dt)
+
+        print "# Thread : ", i
+        for key in sorted(tasktimes.keys()):
+            taskmin = min(tasktimes[key])
+            taskmax = max(tasktimes[key])
+            tasksum = sum(tasktimes[key])
+            print "{0:18s}: {1:7d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+                  .format(key, len(tasktimes[key]), taskmin, taskmax, tasksum,
+                          tasksum / len(tasktimes[key]), tasksum / total_t * 100.0)
+        print
+
+    print "# All threads : "
+    for key in sorted(alltasktimes.keys()):
+        taskmin = min(alltasktimes[key])
+        taskmax = max(alltasktimes[key])
+        tasksum = sum(alltasktimes[key])
+        print "{0:18s}: {1:7d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+              .format(key, len(alltasktimes[key]), taskmin, taskmax, tasksum,
+                      tasksum / len(alltasktimes[key]),
+                      tasksum / (nthread * total_t) * 100.0)
+    print
+
+    #  Dead times.
+    print "# Deadtimes:"
+    print "# no.    : {0:>9s} {1:>9s} {2:>9s} {3:>9s} {4:>9s} {5:>9s}"\
+          .format("count", "minimum", "maximum", "sum", "mean", "percent")
+    alldeadtimes = []
+    for i in range(nthread):
+        deadtimes = []
+        last = 0
+        for task in tasks[i]:
+            dt = task[0] - last
+            deadtimes.append(dt)
+            last = task[1]
+        dt = total_t - last
+        deadtimes.append(dt)
+
+        deadmin = min(deadtimes)
+        deadmax = max(deadtimes)
+        deadsum = sum(deadtimes)
+        print "thread {0:2d}: {1:9d} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.4f} {6:9.2f}"\
+              .format(i, len(deadtimes), deadmin, deadmax, deadsum,
+                      deadsum / len(deadtimes), deadsum / total_t * 100.0)
+        alldeadtimes.extend(deadtimes)
+
+    deadmin = min(alldeadtimes)
+    deadmax = max(alldeadtimes)
+    deadsum = sum(alldeadtimes)
+    print "all      : {0:9d} {1:9.4f} {2:9.4f} {3:9.4f} {4:9.4f} {5:9.2f}"\
+          .format(len(alldeadtimes), deadmin, deadmax, deadsum,
+                  deadsum / len(alldeadtimes),
+              deadsum / (nthread * total_t ) * 100.0)
+    print
+
+
+sys.exit(0)