No speedup on multi-processor machine?

[danfan1981@yahoo.com]

Hi,
I am using Python Thread library for my parallel processing course
project. I am doing matrix convolution on a multi-processor machine
running Solaris. I just found out that no speed-up is obtained with
threading. It is probably because of something called GIL in Python.
How can I get around
that GIL and get speed-up?
Thanks in advance.
Daniel

[Fuzzyman]

Re: No speedup on multi-processor machine?

On Apr 21, 10:53 pm, Dennis Lee Bieber <wlfr...@ix.net com.comwrote:

On 21 Apr 2007 14:02:12 -0700, danfan1...@yaho o.com declaimed the
following in comp.lang.pytho n:
>

Hi,
I am using Python Thread library for my parallel processing course
project. I am doing matrix convolution on a multi-processor machine
running Solaris. I just found out that no speed-up is obtained with
threading. It is probably because of something called GIL in Python.
How can I get around
that GIL and get speed-up?

>
Threading in Python is optimized for I/O bound processing, wherein
the threads spend most of their lives sleeping (blocked waiting for some
I/O to complete, or some lock/event/condition to change state). It is
not optimized for parallel number crunching.
>
Options:
>
Don't use the common "CPython" (eg, the Python built from C-language
source using the C-runtime library). Jython (a version that runs on the
JVM, using Java libraries) may not be afflicted with the GIL.
>

IronPython is *definitely* not restricted by the GIL.

Fuzzyman
http://www.voidspace.org.uk/ironpython/index.shtml

[Caleb Hattingh]

Re: No speedup on multi-processor machine?

On Apr 21, 11:02 pm, danfan1...@yaho o.com wrote:

Hi,
I am using Python Thread library for my parallel processing course
project. I am doing matrix convolution on a multi-processor machine
running Solaris. I just found out that no speed-up is obtained with
threading. It is probably because of something called GIL in Python.
How can I get around
that GIL and get speed-up?
Thanks in advance.
Daniel

Perhaps try

http://www.parallelpython.com/

or

http://www.its.caltech.edu/~astraw/seppo.html

Caleb

[John Nagle]

Re: No speedup on multi-processor machine?

Caleb Hattingh wrote:

On Apr 21, 11:02 pm, danfan1...@yaho o.com wrote:
>

>>Hi,
>>I am using Python Thread library for my parallel processing course
>>project. I am doing matrix convolution on a multi-processor machine
>>running Solaris. I just found out that no speed-up is obtained with
>>threading. It is probably because of something called GIL in Python.
>>How can I get around
>>that GIL and get speed-up?
>>Thanks in advance.
>>Daniel

If you're actually doing the convolution in Python, you need
optimization before you need more CPUs. There's a numerics library
for Python called NumPy, but it doesn't have a convolution function,
although it has an FFT, which may be useful.

But this is just homework. Do something reasonable and turn it
in. A high performance solution to this problem is probably more
work than it's worth.

John Nagle

[Neil Hodgson]

Re: No speedup on multi-processor machine?

Fuzzyman:

IronPython is *definitely* not restricted by the GIL.

IronPython is currently mostly slower than CPython although the
particular problem should be tested to see if IronPython helps.

Some recent benchmarks between IronPython and CPython:

http://sparcs.kaist.ac.kr/~tinuviel/pybench/

Neil

[Fuzzyman]

Re: No speedup on multi-processor machine?

On Apr 22, 1:03 am, Neil Hodgson <nyamatongwe+th un...@gmail.com >
wrote:

Fuzzyman:
>

IronPython is *definitely* not restricted by the GIL.

>
IronPython is currently mostly slower than CPython although the
particular problem should be tested to see if IronPython helps.
>
Some recent benchmarks between IronPython and CPython:http://sparcs.kaist.ac.kr/~tinuviel/pybench/
>

Yep, I've seen that. :-)

http://www.voidspace.org.uk/python/w..._21.shtml#e687

It's not entirely slower, but mainly slower.

OTOH, if you split a job into two threads on a twin-core machine,
IronPython performance will increase dramatically whilst CPython will
go down...

Additionally, extending IronPython from C# is orders of magnitude
easier than extending CPython from C.

Fuzzyman
http://www.voidspace.org.uk/ironpython/index.shtml

Neil

[Grant Edwards]

Re: No speedup on multi-processor machine?

On 2007-04-21, danfan1981@yaho o.com <danfan1981@yah oo.comwrote:

I am using Python Thread library for my parallel processing
course project. I am doing matrix convolution on a
multi-processor machine running Solaris. I just found out that
no speed-up is obtained with threading. It is probably because
of something called GIL in Python. How can I get around that
GIL and get speed-up?

Not much of a parallel processing course. It appears they
haven't taught you anything about parallel processing.

http://wiki.python.org/moin/ParallelProcessing

--
Grant Edwards grante Yow! There's a SALE on
at STRETCH SOCKS down at the
visi.com "7-11"!!

[Robert Kern]

Re: No speedup on multi-processor machine?

John Nagle wrote:

There's a numerics library
for Python called NumPy, but it doesn't have a convolution function,
although it has an FFT, which may be useful.

In [1]: from numpy import *

In [2]: convolve?
Type: function
Base Class: <type 'function'>
Namespace: Interactive
File:
/Library/Frameworks/Python.framewor k/Versions/2.5/lib/python2.5/site-packages/numpy-1.0.3.dev3714-py2.5-macosx-10.3-fat.egg/numpy/core/numeric.py
Definition: convolve(a, v, mode='full')
Docstring:
Returns the discrete, linear convolution of 1-D sequences a and v; mode
can be 'valid', 'same', or 'full' to specify size of the resulting sequence.

--
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco

[danfan1981@yahoo.com]

Re: No speedup on multi-processor machine?

Thanks guys. But I think IronPython only works on Windows machine, but
I am using a Sun machine. I was suggested to use Jython, which can run
on Sun. But I need to use Numpy for matrix operations, which is only
available to CPython.

[Fuzzyman]

Re: No speedup on multi-processor machine?

On Apr 22, 1:03 am, Neil Hodgson <nyamatongwe+th un...@gmail.com >
wrote:

Fuzzyman:
>

IronPython is *definitely* not restricted by the GIL.

>
IronPython is currently mostly slower than CPython although the
particular problem should be tested to see if IronPython helps.
>
Some recent benchmarks between IronPython and CPython:http://sparcs.kaist.ac.kr/~tinuviel/pybench/

Not when running on the .NET platform, there is not a lot of
difference overall:

http://www.voidspace.org.uk/python/w..._21.shtml#e688

Fuzzyman
http://www.voidspace.org.uk/ironpython/index.shtml

>
Neil

[Stefan Behnel]

Re: No speedup on multi-processor machine?

danfan1981@yaho o.com schrieb:

Thanks guys. But I think IronPython only works on Windows machine, but
I am using a Sun machine.

Isn't there a mono port for Sun?

Stefan

[Cameron Laird]

Re: No speedup on multi-processor machine?

In article <EdxWh.5224$2v1 .4151@newssvr14 .news.prodigy.n et>,
John Nagle <nagle@animats. comwrote:

>Caleb Hattingh wrote:

>On Apr 21, 11:02 pm, danfan1...@yaho o.com wrote:
>>

>>>Hi,
>>>I am using Python Thread library for my parallel processing course
>>>project. I am doing matrix convolution on a multi-processor machine
>>>running Solaris. I just found out that no speed-up is obtained with
>>>threading. It is probably because of something called GIL in Python.
>>>How can I get around
>>>that GIL and get speed-up?
>>>Thanks in advance.
>>>Daniel

>
If you're actually doing the convolution in Python, you need
>optimization before you need more CPUs. There's a numerics library
>for Python called NumPy, but it doesn't have a convolution function,
>although it has an FFT, which may be useful.
>
But this is just homework. Do something reasonable and turn it
>in. A high performance solution to this problem is probably more
>work than it's worth.
>
> John Nagle

Along with the excellent advice given by Dennis, John, and the
rest, please be aware that *process*-level parallelization of
a problem sometimes is a benefit. As already recommended, <URL:
http://wiki.python.org/moin/ParallelProcessing touches on most
of the pertinent concepts.

[Klaas]

Re: No speedup on multi-processor machine?

On Apr 21, 5:14 pm, Fuzzyman <fuzzy...@gmail .comwrote:

Additionally, extending IronPython from C# is orders of magnitude
easier than extending CPython from C.

Given the existence of Pyrex, that statement is pretty difficult to
substantiate.

-Mike

[Fuzzyman]

Re: No speedup on multi-processor machine?

On Apr 23, 9:52 pm, Klaas <mike.kl...@gma il.comwrote:

On Apr 21, 5:14 pm, Fuzzyman <fuzzy...@gmail .comwrote:
>

Additionally, extending IronPython from C# is orders of magnitude
easier than extending CPython from C.

>
Given the existence of Pyrex, that statement is pretty difficult to
substantiate.
>

With Pyrex you still need to do memory management for non-Python
types. Additionally compiling C# from within IronPython is *very*easy.

C# is a much easier language to use than C - even with the help of
Pyrex. You use types defined in C# *natively* within IronPython.

All the best,

Fuzzyman
http://www.voidspace.org.uk/python/articles.shtml

-Mike

[Jorgen Grahn]

Re: No speedup on multi-processor machine?

On 23 Apr 2007 13:52:52 -0700, Klaas <mike.klaas@gma il.comwrote:

On Apr 21, 5:14 pm, Fuzzyman <fuzzy...@gmail .comwrote:
>

>Additionally , extending IronPython from C# is orders of magnitude
>easier than extending CPython from C.

>
Given the existence of Pyrex, that statement is pretty difficult to
substantiate.

IMHO, you don't even need Pyrex. When you've done it manually once,
you have the blueprint for your other extension modules. Most of the
work should be normal "fake OOP in C" programming.

Doing it for the first time is another matter, however.

/Jorgen

--
// Jorgen Grahn <grahn@ Ph'nglui mglw'nafh Cthulhu
\X/ snipabacken.dyn dns.org R'lyeh wgah'nagl fhtagn!