On Apr 23, 9:52 pm, Klaas [EMAIL PROTECTED] wrote:
On Apr 21, 5:14 pm, Fuzzyman [EMAIL PROTECTED] wrote:
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
On 23 Apr 2007 13:52:52 -0700, Klaas [EMAIL PROTECTED] wrote:
On Apr 21, 5:14 pm, Fuzzyman [EMAIL PROTECTED] wrote:
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
On Apr 21, 5:14 pm, Fuzzyman [EMAIL PROTECTED] wrote:
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
--
On Apr 22, 1:03 am, Neil Hodgson [EMAIL PROTECTED]
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
In article [EMAIL PROTECTED],
John Nagle [EMAIL PROTECTED] wrote:
Caleb Hattingh wrote:
On Apr 21, 11:02 pm, [EMAIL PROTECTED] 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
[EMAIL PROTECTED] 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
--
http://mail.python.org/mailman/listinfo/python-list
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.
--
http://mail.python.org/mailman/listinfo/python-list
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
On Apr 21, 10:53 pm, Dennis Lee Bieber [EMAIL PROTECTED] wrote:
On 21 Apr 2007 14:02:12 -0700, [EMAIL PROTECTED] declaimed the
following in comp.lang.python:
Hi,
I am using Python Thread library for my parallel processing course
project. I am doing matrix convolution on a multi-processor
On Apr 21, 11:02 pm, [EMAIL PROTECTED] 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
Caleb Hattingh wrote:
On Apr 21, 11:02 pm, [EMAIL PROTECTED] 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
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:
On Apr 22, 1:03 am, Neil Hodgson [EMAIL PROTECTED]
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
On 2007-04-21, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote:
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
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
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