Chih-Che,

The CUDA support in deal.II is very new. It is only in the development 
version of deal (https://github.com/dealii/dealii). You can see our current 
development plan here https://github.com/dealii/dealii/projects/2 Right 
now, we have support for vector and partial support for matrix-free (a good 
place to see the capabilities is the test suite 
https://github.com/dealii/dealii/tree/master/tests/cuda). I would advise 
you to wait for this PR https://github.com/dealii/dealii/pull/4846 to be 
merged before your try to install deal with CUDA. This PR makes it a lot 
easier to install deal with CUDA. If you want to work on CUDA, you should 
work on something that you like / is of interest to you. If you want to 
help our existing effort, you can pick something from this list 
https://github.com/dealii/dealii/issues/4399. I am working on the first 
item but let me know if you find anything else interesting, I can help you 
implementing it.

If you have any questions, please ask. We are looking for people to help us 
with CUDA.

Best,

Bruno

On Monday, August 14, 2017 at 7:56:45 AM UTC-4, Chih-Che Chueh wrote:
>
> Dear deal.II developers and users,
>
> Recently, I spent some spare time assimilating CUDA C programming in the 
> last few months, and I already know very well how to use CUDA stream 
> events to let CPU and kernel (GPU) execution work asynchronously with 
> efficiently overlapping data transfer between CPU and GPU, how to use 
> shared memory to ensure global memory coalescing efficiently, how to map 
> threads to matrix elements either using CARTESIAN x, y, z or a row/column 
> mapping in GPU, as well as how to use shared memory to enhance data 
> reuse. Most importantly, for actual practice, we have a GPU accelerator 
> (i.e. NVIDIA Tesla K40) that was bought last year. I plan to use the CUDA C 
> programming to deal with big data or image identification with artificial 
> intelligence (deep learning) for atmospheric data.
>
> Anyway, I am writing to ask if I could get involved with a deal.II project 
> of people who are working on asynchronous adaptive mesh refinement for 
> acceleration or other performance improvement in deal.II with CUDA C 
> programming.
>
> Thanks!
>
> Sincerely,
>
> Chih-Che
>

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