Hameer Abbasi writes:
> There's ClPy for OpenCL: https://github.com/fixstars/clpy
> Also this pull request for CuPy (merged, but as yet unreleased):
> https://github.com/cupy/cupy/pull/1094
>
This is great hope. Thanks for sharing this.
I wonder why NVIDIA's approach is so widely accepted. Some
On Fri, Oct 18, 2019 at 3:06 AM Ralf Gommers wrote:
>
>
> On Fri, Oct 11, 2019 at 4:18 AM Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Thu, Oct 10, 2019 at 6:02 PM Stefan van der Walt
>> wrote:
>>
>>> On Thu, Oct 10, 2019, at 09:34, Charles R Harris wrote:
>>>
>>> I think
Hi Daniel. Usually one would use python, something like `rng =
np.random.Generator(np.random.PCG64(seed)); a = rng.uniform(10, size=(3,
4))` to get a 3 by 4 array of uniform random numbers in the range of 0 to
10. Is there a reason you need to do this from C?
Matti
--
Sent from: http://numpy-di
Hello Pankaj,
There's ClPy for OpenCL: https://github.com/fixstars/clpy
Also this pull request for CuPy (merged, but as yet unreleased):
https://github.com/cupy/cupy/pull/1094
Best regards,
Hameer Abbasi
On 18.10.19, 12:53, "NumPy-Discussion on behalf of Pankaj Jangid"
wrote:
Is there a
Is there an officially recommended way to utilize AMD GPUs via OpenCL,
ROCm?
I came across ROCm website https://rocm.github.io/. This has Tensorflow
and PyTorch versions for using AMD GPUs. Just wanted to know if there is
a way to use my AMD GPUs for NumPy calculations.
--
Regards,
Pankaj Jangid
On Fri, Oct 11, 2019 at 4:18 AM Charles R Harris
wrote:
>
>
> On Thu, Oct 10, 2019 at 6:02 PM Stefan van der Walt
> wrote:
>
>> On Thu, Oct 10, 2019, at 09:34, Charles R Harris wrote:
>>
>> I think we can support 3.5 as long as we please, the question is how long
>> we *want* to support it. I do
