On 20/09/15 21:48, Sturla Molden wrote:
This is where a small subset of C++ would be handy. Making an uint128_t
class with overloaded operators is a nobrainer. :-)
Meh... The C++ version of PCG already has this.
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On 19/09/15 18:06, Robert Kern wrote:
That said, we'd
probably end up doing a significant amount of rewriting so that we will
have a C implementation of software-uint128 arithmetic.
This is where a small subset of C++ would be handy. Making an uint128_t
class with overloaded operators is a no
On Sat, Sep 19, 2015 at 2:26 PM, Antoine Pitrou wrote:
>
> On Mon, 14 Sep 2015 19:02:58 +0200
> Sturla Molden wrote:
> > On 14/09/15 10:34, Antoine Pitrou wrote:
> >
> > > If Numpy wanted to switch to a different generator, and if Numba
wanted
> > > to remain compatible with Numpy, one of the PCG
On Mon, 14 Sep 2015 19:02:58 +0200
Sturla Molden wrote:
> On 14/09/15 10:34, Antoine Pitrou wrote:
>
> > If Numpy wanted to switch to a different generator, and if Numba wanted
> > to remain compatible with Numpy, one of the PCG functions would be an
> > excellent choice (also for CPU performance
On Mon, Sep 14, 2015 at 7:56 AM, Sturla Molden wrote:
> On 14/09/15 10:34, Antoine Pitrou wrote:
>
>> Currently we don't provide those APIs on the GPU, since MT is much too
>> costly there.
>>
>> If Numpy wanted to switch to a different generator, and if Numba wanted
>> to remain compatible with N
On 14/09/15 10:26, Robert Kern wrote:
I want fast, multiple independent streams on my
current hardware first, and PCG gives that to me.
DCMT is good for that as well.
It should be possible to implement a pluggable design of NumPy's mtrand.
Basically call a function pointer instead of rk_doub
On 14/09/15 10:34, Antoine Pitrou wrote:
If Numpy wanted to switch to a different generator, and if Numba wanted
to remain compatible with Numpy, one of the PCG functions would be an
excellent choice (also for CPU performance, incidentally).
Is Apache license ok in NumPy?
(Not sure, thus aski
On 14/09/15 10:34, Antoine Pitrou wrote:
Currently we don't provide those APIs on the GPU, since MT is much too
costly there.
If Numpy wanted to switch to a different generator, and if Numba wanted
to remain compatible with Numpy, one of the PCG functions would be an
excellent choice (also for
On Mon, 14 Sep 2015 09:26:58 +0100
Robert Kern wrote:
>
> Actually, I meant all of the crap *around* it, the platform-compatibility
> testing to see if you have such a hardware instruction or not, and C++
> template shenanigans in the surrounding code. It's possible that the
> complexity is only
[Tim, ping me if you want to get dropped from the reply chain, as we are
liable to get more into numpy decision-making. I've dropped python-ideas.]
On Mon, Sep 14, 2015 at 4:34 AM, Tim Peters wrote:
>
> [Robert Kern ]
> >> ...
> >> I'll also recommend the PCG paper (and algorithm) as the author's
[This is getting fairly off-topic for python-ideas (since AFAICT there
is no particular reason right now to add a new deterministic generator
to the stdlib), so CC'ing numpy-discussion and I'd suggest followups
be directed to there alone.]
On Thu, Sep 10, 2015 at 10:41 AM, Robert Kern wrote:
> On
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