On 26-May-09, at 1:15 AM, Robert Kern wrote:
I *did* do some due diligence before I designed a new binary format.
Uh oh, I feel this might've taken a sharp turn towards another of
course Robert is right, Robert is always right threads. :)
David
Charles R Harris wrote:
I am trying to put together some rule for parsing text strings/files in
fromfile, fromstring so that the two are consistent.
Thanks for giving these some attention -- they've needed it for a while!
1) When the string/file is empty fromfile returns and empty array,
Not a question really but just for discussion/pie-in-the-sky etc
This is a news item on vizworld about getting Matlab code to run on a
CUDA enabled GPU.
http://www.vizworld.com/2009/05/cuda-enable-matlab-with-gpumat/
If the use of GPU's for numerical tasks takes off (has it already?) then
Brennan Williams wrote:
Not a question really but just for discussion/pie-in-the-sky etc
This is a news item on vizworld about getting Matlab code to run on a
CUDA enabled GPU.
http://www.vizworld.com/2009/05/cuda-enable-matlab-with-gpumat/
There is this which looks similar for
A Tuesday 26 May 2009 03:11:56 David Cournapeau escrigué:
Charles R Harris wrote:
On Mon, May 25, 2009 at 4:59 AM, Andrew Friedley afrie...@indiana.edu
mailto:afrie...@indiana.edu wrote:
For some reason the list seems to occasionally drop my messages...
Francesc Alted wrote:
Francesc Alted wrote:
Well, it is Andrew who should demonstrate that his measurement is correct,
but
in principle, 4 cycles/item *should* be feasible when using 8 cores in
parallel.
But the 100x speed increase is for one core only unless I misread the
table. And I should have mentioned
Also note: nvidia is about to release the first implementation of an OpenCL
runtime based on cuda. OpenCL is an open standard such as OpenGL but for
numerical computing on stream platforms (GPUs, Cell BE, Larrabee, ...).
--
Olivier
On May 26, 2009 8:54 AM, David Cournapeau
Hello,
I've come across what is probably a bug in size check for large arrays:
import numpy
z1 = numpy.zeros((255*256,256*256))
Traceback (most recent call last):
File stdin, line 1, in module
ValueError: dimensions too large.
z2 = numpy.zeros((256*256,256*256))
z2.shape
(65536, 65536)
Olivier Grisel wrote:
Also note: nvidia is about to release the first implementation of an
OpenCL runtime based on cuda. OpenCL is an open standard such as OpenGL
but for numerical computing on stream platforms (GPUs, Cell BE, Larrabee,
...).
You might be interested in pycuda.
On Tue, May 26, 2009 at 07:43:02AM -0400, Neal Becker wrote:
Olivier Grisel wrote:
Also note: nvidia is about to release the first implementation of an
OpenCL runtime based on cuda. OpenCL is an open standard such as OpenGL
but for numerical computing on stream platforms (GPUs, Cell BE,
2009/5/26 Gael Varoquaux gael.varoqu...@normalesup.org:
On Tue, May 26, 2009 at 07:43:02AM -0400, Neal Becker wrote:
Olivier Grisel wrote:
Also note: nvidia is about to release the first implementation of an
OpenCL runtime based on cuda. OpenCL is an open standard such as OpenGL
but for
On Tuesday 26 May 2009 14:08:32 Matthieu Brucher wrote:
2009/5/26 Gael Varoquaux gael.varoqu...@normalesup.org:
On Tue, May 26, 2009 at 07:43:02AM -0400, Neal Becker wrote:
Olivier Grisel wrote:
Also note: nvidia is about to release the first implementation of an
OpenCL runtime based on
The issue with OpenCL is that there will be some extensions for each
supported architecture, which means that the generic OpenCL will never
be very fast or more exactly near the optimum.
what's the difference w/ OpenGL ?
i.e. isn't the job of the underlying library to provide the best
David Cournapeau wrote:
Francesc Alted wrote:
Well, it is Andrew who should demonstrate that his measurement is correct,
but
in principle, 4 cycles/item *should* be feasible when using 8 cores in
parallel.
But the 100x speed increase is for one core only unless I misread the
table. And
Would you like to put xirr in econpy until
it finds a home in SciPy? (Might as well
make it available.)
Cheers,
Alan Isaac
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On Tue, May 26, 2009 at 1:55 AM, Nicolas Rougier
nicolas.roug...@loria.frwrote:
Hello,
I've come across what is probably a bug in size check for large arrays:
import numpy
z1 = numpy.zeros((255*256,256*256))
Traceback (most recent call last):
File stdin, line 1, in module
ValueError:
I rewrote irr to use the iterative solver instead of polynomial roots
so that it can also handle large arrays. For 3000 values, I had to
kill the current np.irr since I didn't want to wait longer than 10
minutes
When writing the test, I found that npv is missing a when keyword,
for the case when
On May 25, 2009, at 10:59 PM, Joe Harrington wrote:
Let's keep this thread focussed on the original issue:
just add a floating array of times to irr or a new xirr
continuous interest
no more
Anyone can use the timeseries package to produce a floating array of
times from normal dates, if
Hi there,
One of our users just found a bug in numpy that has to do with casting.
Consider the attached example.
The difference at the end should be 0 (zero) everywhere.
But it's not by default.
Casting the data to 'float64' at reading and assiging to the arrays
works
Defining the arrays
On Tue, May 26, 2009 at 00:50, Christopher Barker chris.bar...@noaa.gov wrote:
Robert Kern wrote:
Yes. That's why I wrote the NPY format instead. I *did* do some due
diligence before I designed a new binary format.
I assumed so, and I also assume you took a look at netcdf3, but since
it's
2009/5/26 Charles سمير Doutriaux doutria...@llnl.gov:
Hi there,
One of our users just found a bug in numpy that has to do with casting.
Consider the attached example.
The difference at the end should be 0 (zero) everywhere.
But it's not by default.
Casting the data to 'float64' at
Robert Kern wrote:
On Tue, May 26, 2009 at 00:50, Christopher Barker chris.bar...@noaa.gov
wrote:
I assumed so, and I also assume you took a look at netcdf3, but since
it's been brought up here, I take it it didn't fit the bill?
Lack of unsigned and 64-bit integers for the most part. But
Can you teach me how to used array api in C/C++?
1.How to get a data in co-ordinate i,j ,
example
a = array([[1,2,3],[4,5,6]]) how do i get the value of 5 in c/c++
or
2.How i sum all of data in arrays in c/c++
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