Test scaling.py: Difference between revisions

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test_scaling.py 2533 2008-12-07 15:11:10Z
 
Kaihsu (talk | contribs)
use <source/>
 
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Python script that uses [[calc_testjobs_linux.sh]] to benchmark scaling using the ''walp_octane_NPT_sp_MD'' test case. See [[Talk:Performace#Scaling]] for details.
Python script that uses [[calc_testjobs_linux.sh]] to benchmark scaling using the ''walp_octane_NPT_sp_MD'' test case. See [[Talk:Performance#Scaling]] for details.


<pre>#!/usr/bin/env python
<source lang="python">
# $Id: test_scaling.py 2533 2008-12-07 15:11:10Z www-data $
#!/usr/bin/env python
# $Id: test_scaling.py 2534 2008-12-07 15:59:59Z www-data $
# Testing scaling of hippo
# Testing scaling of hippo
# Copyright (c) 2008 Biowerkzeug
# Copyright (c) 2008 Biowerkzeug
Line 42: Line 43:
   walltime = float(m.group('T_SECONDS'))
   walltime = float(m.group('T_SECONDS'))
   runtime[numthreads] = walltime
   runtime[numthreads] = walltime
   scaling = walltime/runtime[1]          # runtime[1] is known after the first iteration!  
   scaling = runtime[1]/walltime           # runtime[1] is known after the first iteration!  
   out.write("%(numthreads)d %(walltime)f %(scaling)f\n" % vars())
   out.write("%(numthreads)d %(walltime)f %(scaling)f\n" % vars())
out.close()
out.close()
Line 69: Line 70:
pylab.savefig(figname)
pylab.savefig(figname)
print "Saved figure "+figname
print "Saved figure "+figname
</pre>
</source>

Latest revision as of 15:43, 8 December 2008

Python script that uses calc_testjobs_linux.sh to benchmark scaling using the walp_octane_NPT_sp_MD test case. See Talk:Performance#Scaling for details.

#!/usr/bin/env python
# $Id: test_scaling.py 2534 2008-12-07 15:59:59Z www-data $
# Testing scaling of hippo
# Copyright (c) 2008 Biowerkzeug
# Oliver Beckstein  <orbeckst@gmail.com>


from subprocess import Popen,PIPE
import sys,re

calc_test_jobs = '/home/oliver/Library/Hippo/Benchmark/calc_testjobs_linux.sh'
hippo_test_case = 'walp_octane_NPT_sp_MD'
filename = "scaling.xvg"
figname = "scaling.png"

try:
  maxslots = int(sys.argv[1])
except:
  print "usage: %s NSLOTS" % sys.argv[0]
  sys.exit(1)

slotrange = (1,maxslots+1) # <--- 1-4 !!

benchmark_pattern = re.compile(r'BENCHMARK:\s*(\w+)\s+(?P<NUMTHREADS>[0-9]+)\s+(?P<T_SECONDS>[0-9.]+)')

runtime = {}
out = open(filename,'w')
out.write("# scaling for Hippo\n# numthreads walltime/s  scaling\n")
for NSLOTS in xrange(*slotrange):
  print "-- running NSLOTS = %(NSLOTS)d" % vars()
  p1 = Popen([calc_test_jobs, '-n', str(NSLOTS), hippo_test_case],stdout=PIPE)
  p2 = Popen(['grep','BENCHMARK:'],stdin=p1.stdout,stdout=PIPE)
  output = p2.communicate()[0]
  m = benchmark_pattern.match(output)
  print "output: ",output,
  if not m:
      print "ERROR: no benchmark data found"
      continue    
  numthreads = int(m.group('NUMTHREADS'))
  walltime = float(m.group('T_SECONDS'))
  runtime[numthreads] = walltime
  scaling = runtime[1]/walltime           # runtime[1] is known after the first iteration! 
  out.write("%(numthreads)d %(walltime)f %(scaling)f\n" % vars())
out.close()

# Analysis
import numpy
import pylab
N = numpy.sort(runtime.keys())
T = numpy.array([runtime[n] for n in N],dtype=float)
S = T[0]/T

pylab.clf()

pylab.subplot(211)
pylab.title('Hippo test case: '+hippo_test_case)
pylab.xlabel('cpus')
pylab.ylabel('walltime/s')
pylab.plot(N,T,'ro-')

pylab.subplot(212)
pylab.xlabel('cpus')
pylab.ylabel('scaling')
pylab.plot(N,S,'ro-')
pylab.plot([N[0],N[-1]], [1,N[-1]], 'k--')

pylab.savefig(figname)
print "Saved figure "+figname