grain - D Language for Deep Learning

[Shigeki Karita]

On Wednesday, 24 April 2019 at 17:31:03 UTC, jmh530 wrote:
> On Wednesday, 24 April 2019 at 16:33:00 UTC, Shigeki Karita 
> wrote:
>> [snip]
>>
>> I see. I'm interested in Stan that is the best library for 
>> probabilistic models but it lacks of GPU computation. 
>> Therefore, I plan to add some probabilistic programming 
>> paradigm into grain like pytorch (pyro) and tensorflow (tf 
>> probability).
>
> Conveniently enough, they just incorporated some GPU support in 
> the release in March [1]. Here's an earlier status update [2]. 
> The initial work was focused on cholesky decomposition because 
> that was a big source of slowdown for some types of models. 
> Probably still has a ways to go before reaching tensorflows 
> maturity on the GPU.
>
> [1] https://github.com/stan-dev/math/releases/tag/v2.19.0
> [2] 
> https://discourse.mc-stan.org/t/gpu-update-whats-up-and-where-we-are-going/6015

I haven't know that GPU support in Stan. That's Cool! Cholesky 
decomposition always suffers me when I use covariance matrix or 
something. If you are interested in GPU acceleration in 
probabilistic programming, see also this paper (Table 2) of 
Edward (previous name of Tensorflow Probability) 
https://arxiv.org/pdf/1701.03757.pdf