Hi all,
> And yet, Java programmers manage to write threaded applications all
> day long without getting bitten (once they're used to the issues),
> despite usually being less skilled than Python programmers ;-).
> These days, even semi-entry-level consumer laptop computers have dual
> core CPU's, and quad Opteron boxes (8-way multiprocessing using X2
> processors) are quite affordable for midrange servers or engineering
> workstations, and there's endless desire to write fancy server apps
> completely in Python. There is no point paying for all that
> multiprocessor hardware if your programming language won't let you use
> it. So, Python must punt the GIL if it doesn't want to keep
> presenting undue obstacles to writing serious apps on modern hardware.
True
GIL implementation must have got its own good causes as it it designed
but as language evolves its very essential that one increases the
scope such that it fits into many usage areas(eg. scientific
applications using multiprocessors etc.).
In the modern scientific age where
__multiprocessor_execution_environment__ is quite common, i feel there
is a need to rethink abt the introduction of true parallelization
capabilities in python.
I know many of my friends who didnot choose python for obvious reasons
of the nature of thread execution in the presence of GIL which means
that one is wasting sophisticated hardware resources.
##########################################
if __name__ == ''__multiprocessor_execution_environment__':
for python_version in range(python2.4.x, python3.x, x):
if python_version.GIL:
print 'unusable for computation intensive multiprocessor
architecture'
else:
print cmp(python,java)
############################################
regards,
KM
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