Commit 8ab0ae26 authored by James Willis's avatar James Willis
Browse files

Moved script to examples/

parent aa04e260
#!/usr/bin/env python
#
# Usage:
# python plot_scaling_results.py input-file1-ext input-file2-ext ...
#
# Description:
# Plots speed up, parallel efficiency and time to solution given a "timesteps" output file generated by SWIFT.
#
# Example:
# python plot_scaling_results.py _hreads_cosma_stdout.txt _threads_knl_stdout.txt
#
# The working directory should contain files 1_threads_cosma_stdout.txt - 64_threads_cosma_stdout.txt and 1_threads_knl_stdout.txt - 64_threads_knl_stdout.txt, i.e wall clock time for each run using a given number of threads
import sys
import glob
import re
import numpy as np
import matplotlib.pyplot as plt
version = []
branch = []
revision = []
hydro_scheme = []
hydro_kernel = []
hydro_neighbours = []
hydro_eta = []
threadList = []
linestyle = ('ro-','bo-','go-','yo-','mo-')
cmdLine = './swift_fixdt -s -t 16 cosmoVolume.yml'
platform = 'KNL'
# Work out how many data series there are
if len(sys.argv) == 2:
inputFileNames = (sys.argv[1],"")
numOfSeries = 1
elif len(sys.argv) == 3:
inputFileNames = (sys.argv[1],sys.argv[2])
numOfSeries = 2
elif len(sys.argv) == 4:
inputFileNames = (sys.argv[1],sys.argv[2],sys.argv[3])
numOfSeries = 3
elif len(sys.argv) == 5:
inputFileNames = (sys.argv[1],sys.argv[2],sys.argv[3],sys.argv[4])
numOfSeries = 4
elif len(sys.argv) == 6:
inputFileNames = (sys.argv[1],sys.argv[2],sys.argv[3],sys.argv[4],sys.argv[5])
numOfSeries = 5
# Get the names of the branch, Git revision, hydro scheme and hydro kernel
def parse_header(inputFile):
with open(inputFile, 'r') as f:
found_end = False
for line in f:
if 'Branch:' in line:
s = line.split()
branch.append(s[2])
elif 'Revision:' in line:
s = line.split()
revision.append(s[2])
elif 'Hydrodynamic scheme:' in line:
line = line[2:-1]
s = line.split()
line = s[2:]
hydro_scheme.append(" ".join(line))
elif 'Hydrodynamic kernel:' in line:
line = line[2:-1]
s = line.split()
line = s[2:5]
hydro_kernel.append(" ".join(line))
elif 'neighbours:' in line:
s = line.split()
hydro_neighbours.append(s[4])
elif 'Eta:' in line:
s = line.split()
hydro_eta.append(s[2])
return
# Parse file and return total time taken, speed up and parallel efficiency
def parse_files():
times = []
totalTime = []
serialTime = []
speedUp = []
parallelEff = []
for i in range(0,numOfSeries): # Loop over each data series
# Get each file that starts with the cmd line arg
file_list = glob.glob(inputFileNames[i] + "*")
threadList.append([])
# Create a list of threads using the list of files
for fileName in file_list:
s = re.split(r'[_.]+',fileName)
threadList[i].append(int(s[1]))
# Sort the thread list in ascending order and save the indices
sorted_indices = np.argsort(threadList[i])
threadList[i].sort()
# Sort the file list in ascending order acording to the thread number
file_list = [ file_list[j] for j in sorted_indices]
parse_header(file_list[0])
version.append(branch[i] + " " + revision[i] + "\n" + hydro_scheme[i] +
"\n" + hydro_kernel[i] + r", $N_{neigh}$=" + hydro_neighbours[i] +
r", $\eta$=" + hydro_eta[i] + "\n")
times.append([])
totalTime.append([])
speedUp.append([])
parallelEff.append([])
# Loop over all files for a given series and load the times
for j in range(0,len(file_list)):
times[i].append([])
times[i][j].append(np.loadtxt(file_list[j],usecols=(5,)))
totalTime[i].append(np.sum(times[i][j]))
serialTime.append(totalTime[i][0])
# Loop over all files for a given series and calculate speed up and parallel efficiency
for j in range(0,len(file_list)):
speedUp[i].append(serialTime[i] / totalTime[i][j])
parallelEff[i].append(speedUp[i][j] / threadList[i][j])
return (times,totalTime,speedUp,parallelEff)
def print_results(times,totalTime,parallelEff,version):
for i in range(0,numOfSeries):
print " "
print "------------------------------------"
print version[i]
print "------------------------------------"
print "Wall clock time for: {} time steps".format(len(times[0][0][0]))
print "------------------------------------"
for j in range(0,len(threadList[i])):
print str(threadList[i][j]) + " threads: {}".format(totalTime[i][j])
print " "
print "------------------------------------"
print "Parallel Efficiency for: {} time steps".format(len(times[0][0][0]))
print "------------------------------------"
for j in range(0,len(threadList[i])):
print str(threadList[i][j]) + " threads: {}".format(parallelEff[i][j])
return
def plot_results(times,totalTime,speedUp,parallelEff):
fig, axarr = plt.subplots(2, 2,figsize=(15,15))
speedUpPlot = axarr[0, 0]
parallelEffPlot = axarr[0, 1]
totalTimePlot = axarr[1, 0]
emptyPlot = axarr[1, 1]
# Plot speed up
for i in range(0,numOfSeries):
speedUpPlot.plot(threadList[i],speedUp[i],linestyle[i],label=version[i])
speedUpPlot.plot(threadList[i],threadList[i],color='k',linestyle='--')
speedUpPlot.set_ylabel("Speed Up")
speedUpPlot.set_xlabel("No. of Threads")
# Plot parallel efficiency
for i in range(0,numOfSeries):
parallelEffPlot.plot(threadList[i],parallelEff[i],linestyle[i])
parallelEffPlot.set_xscale('log')
parallelEffPlot.set_ylabel("Parallel Efficiency")
parallelEffPlot.set_xlabel("No. of Threads")
parallelEffPlot.set_ylim([0,1.1])
# Plot time to solution
for i in range(0,numOfSeries):
totalTimePlot.loglog(threadList[i],totalTime[i],linestyle[i],label=version[i])
totalTimePlot.set_xscale('log')
totalTimePlot.set_xlabel("No. of Threads")
totalTimePlot.set_ylabel("Time to Solution (ms)")
totalTimePlot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.,prop={'size':14})
emptyPlot.axis('off')
for i, txt in enumerate(threadList[0]):
speedUpPlot.annotate(txt, (threadList[0][i],speedUp[0][i]))
parallelEffPlot.annotate(txt, (threadList[0][i],parallelEff[0][i]))
totalTimePlot.annotate(txt, (threadList[0][i],totalTime[0][i]))
fig.suptitle("Thread Speed Up, Parallel Efficiency and Time To Solution for {} Time Steps of Cosmo Volume\n Cmd Line: {}, Platform: {}".format(len(times[0][0][0]),cmdLine,platform))
return
# Calculate results
(times,totalTime,speedUp,parallelEff) = parse_files()
plot_results(times,totalTime,speedUp,parallelEff)
print_results(times,totalTime,parallelEff,version)
plt.show()
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