diff --git a/examples/analyse_tasks.py b/examples/analyse_tasks.py
new file mode 100755
index 0000000000000000000000000000000000000000..0dbd08630f148e9d038a55f2d383593e91a2b6a2
--- /dev/null
+++ b/examples/analyse_tasks.py
@@ -0,0 +1,180 @@
+#!/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)
diff --git a/examples/analyse_tasks_MPI.py b/examples/analyse_tasks_MPI.py
new file mode 100755
index 0000000000000000000000000000000000000000..7063308787b64874c02be159a2153d8d1018a166
--- /dev/null
+++ b/examples/analyse_tasks_MPI.py
@@ -0,0 +1,195 @@
+#!/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)