Dear Andreas Kloeckner:
Thanks for your reply. I was using the plain vanilla Python interpreter,
not the IPython interpreter.
Evidently,
del ary
at the end of the script makes this problem go away. I will have to
remember to do that when I'm exploring pycuda interactively when using a
lot of memory.
Thanks for the tip and all the great work!
On 9/16/2010 7:26 AM, Andreas Kloeckner wrote:
On Wed, 15 Sep 2010 15:36:26 -0700, reckoner<recko...@gmail.com> wrote:
Hi,
Note below what happens when I run fill_gpu_with_nans.py as a script:
c:\>python fill_gpu_with_nans.py
filled 237043712 out of 239140864 bytes with NaNs
however, if I start an interpreter:
c:\>python
Python 2.6.2 (r262:71605, Apr 14 2009, 22:40:02) [MSC v.1500 32 bit
(Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import fill_gpu_with_nans
filled 237043712 out of 239140864 bytes with NaNs
>>> reload ( fill_gpu_with_nans)
filled 983040 out of 1114112 bytes with NaNs
<module 'fill_gpu_with_nans' from 'fill_gpu_with_nans.pyc'>
>>> reload ( fill_gpu_with_nans)
filled 1110016 out of 1114112 bytes with NaNs
<module 'fill_gpu_with_nans' from 'fill_gpu_with_nans.pyc'>
Thus, when run as a script, I get:
filled 237043712 out of 239140864 bytes with NaNs
but from inside the interpreter, I get:
filled 237043712 out of 239140864 bytes with NaNs
filled 983040 out of 1114112 bytes with NaNs
filled 1110016 out of 1114112 bytes with NaNs
What do you mean by 'from inside the interpreter'? Via IPython? Does
IPython preserve the variables from the last execution? See what happens
if you add 'del ary' to the fill script.
Andreas
_______________________________________________
PyCUDA mailing list
PyCUDA@tiker.net
http://lists.tiker.net/listinfo/pycuda
