Hello
from gpunumpy import *
x=zeros(100,dtype='gpufloat') # Creates an array of 100 elements on the GPU
y=ones(100,dtype='gpufloat')
z=exp(2*x+y) # z in on the GPU, all operations on GPU with no transfer
z_cpu=array(z,dtype='float') # z is copied to the CPU
i=(z2.3).nonzero()[0] # operation
2009/8/21 Nicolas Pinto pi...@mit.edu:
For those of you who are interested, we forked python-cuda recently and
started to add some numpy sugar. The goal of python-cuda is to
*complement* PyCuda by providing an equivalent to the CUDA Runtime API
(understand: not Pythonic) using
Agreed! What would be the best name? Our package will provide non-pythonic
bindings to cuda (e.g. import cuda; cuda.cudaMemcpy( ... ) ) and some numpy
sugar (e.g. from cuda import sugar; sugar.fft.fftconvolve(ndarray_a,
ndarray_b, 'same')).
How about cuda-ctypes or ctypes-cuda? Any suggestion?
Olivier Grisel wrote:
As usual, MS reinvents the wheel with DirectX Compute but vendors such
as AMD and nvidia propose both the OpenCL API +runtime binaries for
windows and their DirectX Compute counterpart, based on mostly the
same underlying implementation, e.g. CUDA in nvidia's case.
Charles R Harris charlesr.harris at gmail.com writes:
What sort of functionality are you looking for? It could be you could slip in
a small mod that would do what you want. In the larger picture, the use of GPUs
has been discussed on the list several times going back at least a year. The
main
Ian Mallett geometrian at gmail.com writes:
On Wed, Aug 5, 2009 at 11:34 AM, Charles R Harris charlesr.harris at
gmail.com wrote:
It could be you could slip in a small mod that would do what you want.
I'll help, if you want. I'm good with GPUs, and I'd appreciate the numerical
power
David Warde-Farley dwf at cs.toronto.edu writes:
It did inspire some of our colleagues in Montreal to create this,
though:
http://code.google.com/p/cuda-ndarray/
I gather it is VERY early in development, but I'm sure they'd love
contributions!
Hi David,
That does look quite
Hi everyone,
I was wondering if you had any plan to incorporate some GPU support to numpy, or
perhaps as a separate module. What I have in mind is something that would mimick
the syntax of numpy arrays, with a new dtype (gpufloat), like this:
from gpunumpy import *
x=zeros(100,dtype='gpufloat')
On Wed, Aug 5, 2009 at 4:45 AM, Romain Brette romain.bre...@ens.fr wrote:
Hi everyone,
I was wondering if you had any plan to incorporate some GPU support to
numpy, or
perhaps as a separate module. What I have in mind is something that would
mimick
the syntax of numpy arrays, with a new
On Wed, Aug 5, 2009 at 11:34 AM, Charles R Harris charlesr.har...@gmail.com
wrote:
It could be you could slip in a small mod that would do what you want.
I'll help, if you want. I'm good with GPUs, and I'd appreciate the
numerical power it would afford.
The main problems with using GPUs
With OpenCL implementations making their way into the wild, that's probably
a better target than CUDA.
On Wed, Aug 5, 2009 at 3:39 PM, Ian Mallett geometr...@gmail.com wrote:
On Wed, Aug 5, 2009 at 11:34 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
It could be you could slip in a
A friend of mine wrote a simple wrapper around CUBLAS using ctypes
that basically exposes a Python class that keeps a 2D array of single-
precision floats on the GPU for you, and lets you I keep telling him
to release it, but he thinks it's too hackish.
It did inspire some of our colleagues
OpenCL is definitely the way to go for a cross platform solution with
both nvidia and AMD having released beta runtimes to their respective
developer networks (free as in beer subscription required for the beta
dowload pages). Final public releases to be expected around 2009 Q3.
OpenCL is an open
Olivier Grisel wrote:
OpenCL is definitely the way to go for a cross platform solution with
both nvidia and AMD having released beta runtimes to their respective
developer networks (free as in beer subscription required for the beta
dowload pages). Final public releases to be expected around
2009/8/6 David Cournapeau da...@ar.media.kyoto-u.ac.jp:
Olivier Grisel wrote:
OpenCL is definitely the way to go for a cross platform solution with
both nvidia and AMD having released beta runtimes to their respective
developer networks (free as in beer subscription required for the beta
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