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Re: Different execution time in python code between embedded orstandalone

En Tue, 03 Jun 2008 16:58:12 -0300, Pau Freixes <pf******@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

Jun 27 '08 #1
0 1012

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