Different execution time in python code between embedded or standalone
Gabriel Genellina
gagsl-py2 at yahoo.com.ar
Tue Jun 3 22:45:16 EDT 2008
En Tue, 03 Jun 2008 16:58:12 -0300, Pau Freixes <pfreixes at milnou.net>
escribió:
> Hi list,
>
> First Hello to all, this is my and hope not end message to the list :P
>
> This last months I have been writting a program in c like to mod_python
> for
> embedding python language, it's a middleware for dispatch and execute
> python
> batch programs into several nodes. Now I'm writing some python program
> for
> test how scale this into several nodes and comparing with "standalone"
> performance.
>
> I found a very strange problem with one application named md5challenge,
> this
> aplication try to calculate the max number md5 digest in several seconds,
> md5challenge use a simple signal alarm for stop program when time has
> passed. This is the code of python script
>
> def handler_alrm(signum, frame):
> global _signal
> global _nrdigest
> global _f
>
>
> _signal = True
>
> def try_me():
> global _nrdigest
> global _f
> global _signal
>
> _f = open("/dev/urandom","r")
> while _signal is not True:
> buff = _f.read(_const_b)
> md5.md5(buff).hexdigest()
> _nrdigest = _nrdigest + 1
>
> if _f is not None :
> _f.close()
>
> def main( req ):
> global _nrdigest
>
>
> signal.signal(signal.SIGALRM, handler_alrm)
> signal.alarm(req.input['time'])
>
>
> try_me()
>
> req.output['count'] = _nrdigest
>
> return req.OK
>
>
> if __name__ == "__main__":
>
> # test code
> class test_req:
> pass
>
> req = test_req()
> req.input = { 'time' : 10 }
> req.output = { 'ret' : 0, 'count' : 0 }
> req.OK = 1
>
> main(req)
>
> print "Reached %d digests" % req.output['count']
>
>
> When I try to run this program in standalone into my Pentium Dual Core
> md4challenge reached 1.000.000 milion keys in 10 seconds but when i try
> to
> run this in embedded mode md5challenge reached about 200.000 more keys
> !!! I
> repeat this test many times and always wins embedded mode !!! What's
> happen ?
>
> Also I tested to erase read dependencies from /dev/random, and calculate
> all
> keys from same buffer. In this case embedded mode win always also, and
> the
> difference are more bigger !!!
>
> Thks to all, can anybody help to me ?
So the above code corresponds to the standalone version - what about the
embedded version? Are you sure it is exactly the *same* code? All those
global statements are suspicious, and you don't even need most of them.
Note that looking up a name in the global namespace is much slower than
using a local name.
Also, you're including the time it takes the OS to *generate* several
megabytes of random data from /dev/urandom (how big is _const_b?).
Usually it's easier (and more accurate) to measure the time it takes to
compute a long task (let's say, how much time it takes to compute 1000000
md5 values). You're doing it backwards instead.
I'd rewrite the test as:
def try_me():
from md5 import md5
buff = os.urandom(_const_b)
for i in xrange(1000000):
md5(buff).hexdigest()
def main(req):
t0 = time.clock()
try_me()
t1 = time.clock()
# elapsed time = t1-t0
PS: Recuerdo que respondí esto en la lista de Python en castellano, pero
ahora veo que mi mensaje nunca llegó :(
--
Gabriel Genellina
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