On 12/20/12 7:35 PM, Henry Gomersall wrote:
On Thu, 2012-12-20 at 15:23 +0100, Francesc Alted wrote:
On 12/20/12 9:53 AM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned
arrays
is
for machines
On Fri, 2012-12-21 at 11:34 +0100, Francesc Alted wrote:
Also this convolution code:
https://github.com/hgomersall/SSE-convolution/blob/master/convolve.c
Shows a small but repeatable speed-up (a few %) when using some
aligned
loads (as many as I can work out to use!).
Okay, so a 15%
On 12/21/12 11:58 AM, Henry Gomersall wrote:
On Fri, 2012-12-21 at 11:34 +0100, Francesc Alted wrote:
Also this convolution code:
https://github.com/hgomersall/SSE-convolution/blob/master/convolve.c
Shows a small but repeatable speed-up (a few %) when using some
aligned
loads (as many as I
On 12/20/2012 03:23 PM, Francesc Alted wrote:
On 12/20/12 9:53 AM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned arrays
is
for machines having AVX. But provided that the Intel architecture is
On 12/21/12 1:35 PM, Dag Sverre Seljebotn wrote:
On 12/20/2012 03:23 PM, Francesc Alted wrote:
On 12/20/12 9:53 AM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned arrays
is
for machines having AVX.
On Wed, 2012-12-19 at 15:10 +, Nathaniel Smith wrote:
snip
Is this something that can be rolled into Numpy (the feature, not
my
particular implementation or interface - though I'd be happy for
it to
be so)?
Regarding (b), I've written a test case that works for Linux on
On Thu, 2012-12-20 at 08:12 +, Henry Gomersall wrote:
On Wed, 2012-12-19 at 15:10 +, Nathaniel Smith wrote:
snip
Is this something that can be rolled into Numpy (the feature,
not
my
particular implementation or interface - though I'd be happy
for
it to
be so)?
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned arrays
is
for machines having AVX. But provided that the Intel architecture is
making great strides in fetching unaligned data, I'd be surprised
that
the difference in
On Thu, Dec 20, 2012 at 8:12 AM, Henry Gomersall h...@cantab.net wrote:
On Wed, 2012-12-19 at 15:10 +, Nathaniel Smith wrote:
snip
Is this something that can be rolled into Numpy (the feature, not
my
particular implementation or interface - though I'd be happy for
it to
be so)?
On 12/20/12 9:53 AM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned arrays
is
for machines having AVX. But provided that the Intel architecture is
making great strides in fetching unaligned data,
On 19.12.2012 09:40, Henry Gomersall wrote:
I've written a few simple cython routines for assisting in creating
byte-aligned numpy arrays. The point being for the arrays to work with
SSE/AVX code.
https://github.com/hgomersall/pyFFTW/blob/master/pyfftw/utils.pxi
Why use Cython?
On Thu, 2012-12-20 at 17:26 +0100, Sturla Molden wrote:
On 19.12.2012 09:40, Henry Gomersall wrote:
I've written a few simple cython routines for assisting in creating
byte-aligned numpy arrays. The point being for the arrays to work
with
SSE/AVX code.
On Thu, 2012-12-20 at 17:26 +0100, Sturla Molden wrote:
return tmp[offset:offset+N]\
.view(dtype=d)\
.reshape(shape, order=order)
Also, just for the email record, that should be
return tmp[offset:offset+N*d.itemsize]\
On 19.12.2012 19:25, Henry Gomersall wrote:
That is not true at least under Windows 32-bit. I think also it's not
true for Linux 32-bit from my vague recollections of testing in a
virtual machine. (disclaimer: both those statements _may_ be out of
date).
malloc is required to return memory
On 20.12.2012 17:47, Henry Gomersall wrote:
On Thu, 2012-12-20 at 17:26 +0100, Sturla Molden wrote:
return tmp[offset:offset+N]\
.view(dtype=d)\
.reshape(shape, order=order)
Also, just for the email record, that should be
return
On Thu, 2012-12-20 at 17:48 +0100, Sturla Molden wrote:
On 19.12.2012 19:25, Henry Gomersall wrote:
That is not true at least under Windows 32-bit. I think also it's
not
true for Linux 32-bit from my vague recollections of testing in a
virtual machine. (disclaimer: both those statements
On Thu, 2012-12-20 at 15:23 +0100, Francesc Alted wrote:
On 12/20/12 9:53 AM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
The only scenario that I see that this would create unaligned
arrays
is
for machines having AVX. But provided that the Intel
On 20.12.2012 18:38, Henry Gomersall wrote:
Except I build with MinGW. Please don't tell me I need to install Visual
Studio... I have about 1GB free on my windows partition!
The same DLL is used as CRT.
Sturla
___
NumPy-Discussion mailing list
On Thu, 2012-12-20 at 20:50 +0100, Sturla Molden wrote:
On 20.12.2012 18:38, Henry Gomersall wrote:
Except I build with MinGW. Please don't tell me I need to install
Visual
Studio... I have about 1GB free on my windows partition!
The same DLL is used as CRT.
Perhaps the DLL should go
On 20.12.2012 20:52, Henry Gomersall wrote:
Perhaps the DLL should go and read MS's edicts!
Do you link with same same CRT as Python? (msvcr90.dll)
You should always use -lmsvcr90.
If you don't, you will link with msvcrt.dll.
Sturla
___
On Thu, 2012-12-20 at 20:57 +0100, Sturla Molden wrote:
On 20.12.2012 20:52, Henry Gomersall wrote:
Perhaps the DLL should go and read MS's edicts!
Do you link with same same CRT as Python? (msvcr90.dll)
You should always use -lmsvcr90.
If you don't, you will link with msvcrt.dll.
On 20.12.2012 20:57, Sturla Molden wrote:
On 20.12.2012 20:52, Henry Gomersall wrote:
Perhaps the DLL should go and read MS's edicts!
Do you link with same same CRT as Python? (msvcr90.dll)
You should always use -lmsvcr90.
If you don't, you will link with msvcrt.dll.
Here is VS2008,
On Thu, 2012-12-20 at 21:05 +0100, Sturla Molden wrote:
On 20.12.2012 20:57, Sturla Molden wrote:
On 20.12.2012 20:52, Henry Gomersall wrote:
Perhaps the DLL should go and read MS's edicts!
Do you link with same same CRT as Python? (msvcr90.dll)
You should always use -lmsvcr90.
On 20.12.2012 21:03, Henry Gomersall wrote:
Why is it important? (for my own understanding)
Because if CRT resources are shared between different CRT versions, bad
things will happen (the ABIs are not equivalent, errno and other globals
are at different addresses, etc.) Cython code tends to
On 20.12.2012 21:13, Sturla Molden wrote:
Because if CRT resources are shared between different CRT versions, bad
things will happen (the ABIs are not equivalent, errno and other globals
are at different addresses, etc.)
For example, PyErr_SetFromErrno will return garbage if CRTs are shared.
On Thu, 2012-12-20 at 21:13 +0100, Sturla Molden wrote:
On 20.12.2012 21:03, Henry Gomersall wrote:
Why is it important? (for my own understanding)
Because if CRT resources are shared between different CRT versions,
bad
things will happen (the ABIs are not equivalent, errno and other
On 20.12.2012 21:24, Henry Gomersall wrote:
I didn't know that. It's a real pain having so many libc libs knocking
around. I have little experience of Windows, as you may have guessed!
Originally there was only one system-wide CRT on Windows (msvcrt.dll),
which is why MinGW linkes with that
On Thu, 2012-12-20 at 21:45 +0100, Sturla Molden wrote:
On 20.12.2012 21:24, Henry Gomersall wrote:
I didn't know that. It's a real pain having so many libc libs
knocking
around. I have little experience of Windows, as you may have
guessed!
Originally there was only one system-wide CRT
I've written a few simple cython routines for assisting in creating
byte-aligned numpy arrays. The point being for the arrays to work with
SSE/AVX code.
https://github.com/hgomersall/pyFFTW/blob/master/pyfftw/utils.pxi
The change recently has been to add a check on the CPU as to what flags
are
On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall h...@cantab.net wrote:
I've written a few simple cython routines for assisting in creating
byte-aligned numpy arrays. The point being for the arrays to work with
SSE/AVX code.
https://github.com/hgomersall/pyFFTW/blob/master/pyfftw/utils.pxi
On Wed, Dec 19, 2012 at 7:43 AM, Nathaniel Smith n...@pobox.com wrote:
On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall h...@cantab.net wrote:
I've written a few simple cython routines for assisting in creating
byte-aligned numpy arrays. The point being for the arrays to work with
SSE/AVX
On Wed, Dec 19, 2012 at 2:57 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Dec 19, 2012 at 7:43 AM, Nathaniel Smith n...@pobox.com wrote:
On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall h...@cantab.net wrote:
I've written a few simple cython routines for assisting in
On Wed, Dec 19, 2012 at 8:10 AM, Nathaniel Smith n...@pobox.com wrote:
On Wed, Dec 19, 2012 at 2:57 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Dec 19, 2012 at 7:43 AM, Nathaniel Smith n...@pobox.com wrote:
On Wed, Dec 19, 2012 at 8:40 AM, Henry Gomersall
On Wed, Dec 19, 2012 at 3:27 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Dec 19, 2012 at 8:10 AM, Nathaniel Smith n...@pobox.com wrote:
Right, my intuition is that it's like order=C -- if you make a new
array by, say, indexing, then it may or may not have order=C, no
On Wed, 2012-12-19 at 15:57 +, Nathaniel Smith wrote:
Not sure which interface is more useful to users. On the one hand,
using funny dtypes makes regular non-SIMD access more cumbersome, and
it forces your array size to be a multiple of the SIMD word size,
which might be inconvenient if
On 12/19/12 5:47 PM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 15:57 +, Nathaniel Smith wrote:
Not sure which interface is more useful to users. On the one hand,
using funny dtypes makes regular non-SIMD access more cumbersome, and
it forces your array size to be a multiple of the SIMD
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
snip
Finally, I think there is significant value in auto-aligning the
array
based on an appropriate inspection of the cpu capabilities (or
alternatively, a function that reports back the appropriate SIMD
alignment). Again, this
On Wed, Dec 19, 2012 at 6:25 PM, Henry Gomersall h...@cantab.net wrote:
On Wed, 2012-12-19 at 19:03 +0100, Francesc Alted wrote:
snip
Finally, I think there is significant value in auto-aligning the
array
based on an appropriate inspection of the cpu capabilities (or
alternatively, a
On Wed, Dec 19, 2012 at 6:03 PM, Francesc Alted franc...@continuum.io wrote:
On 12/19/12 5:47 PM, Henry Gomersall wrote:
On Wed, 2012-12-19 at 15:57 +, Nathaniel Smith wrote:
Not sure which interface is more useful to users. On the one hand,
using funny dtypes makes regular non-SIMD access
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