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?
At
2009/8/21 Nicolas Pinto :
> 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 automatically-generated
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=(z>2.3).nonzero()[0] # oper
David Warde-Farley 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
Ian Mallett gmail.com> writes:
>
>
> On Wed, Aug 5, 2009 at 11:34 AM, Charles R Harris
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.
Tha
Charles R Harris 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 problems with us
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.
>
>
2009/8/6 David Cournapeau :
> 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 pu
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 aroun
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
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 i
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 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 small mod that
On Wed, Aug 5, 2009 at 11:34 AM, Charles R Harris 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 were that CUDA was only avai
On Wed, Aug 5, 2009 at 4:45 AM, Romain Brette 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 dtype (gpufloat)
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') #
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