On 31.01.2018 17:58, Chris Barker wrote:
> I'm guessing you could use Cython to make this easier.
... or Boost.Python (http://boostorg.github.io/python), which has
built-in support for NumPy
(http://boostorg.github.io/python/doc/html/numpy/index.html), and
supports both directions: extending Pytho
On 02.01.2018 16:36, Matthieu Brucher wrote:
> Hi,
>
> Let's say that Numpy provides a GPU version on GPU. How would that
> work with all the packages that expect the memory to be allocated on CPU?
> It's not that Numpy refuses a GPU implementation, it's that it
> wouldn't solve the problem of GPU/
On 02.01.2018 15:22, Jerome Kieffer wrote:
> On Tue, 02 Jan 2018 15:37:16 +
> Yasunori Endo wrote:
>
>> If the reason is just about human resources,
>> I'd like to try implementing GPU support on my NumPy fork.
>> My goal is to create standard NumPy interface which supports
>> both CUDA and Op
