Hello, Mike
Thanks a lot for the info!
I'll look into that.
On Wed, Sep 6, 2017 at 4:20 PM, Chu, Mike <[email protected]> wrote:
> Hi Hui,
>
>
>
> We have a fork of Chapel available on the ROCm github. You do need ROCm
> and an AMD APU to run these today. The code is available here:
>
> https://github.com/ROCm-Developer-Tools/chapel/tree/chpl-hsa-master
>
>
>
> Code examples which run on the GPU are here:
>
> https://github.com/ROCm-Developer-Tools/chapel/tree/
> chpl-hsa-master/test/release/examples/hsa
>
>
>
> Right now, our code is working on the Chapel-to-C path, so it does not
> work on the LLVM path. We’re working on merging our changes back to
> master.
>
>
>
> Mike.
>
>
>
> *From:* Hui Zhang [mailto:[email protected]]
> *Sent:* Tuesday, September 5, 2017 5:09 AM
> *To:* Chapel Sourceforge Developers List <chapel-developers@lists.
> sourceforge.net>
> *Subject:* [Chapel-developers] Chapel support on GPU
>
>
>
> Hello,
>
>
>
> I need some information and suggestions about the Chapel's support on GPU.
> (I had zero knowledge of GPU)
>
>
>
> After doing some research, I only found two separate works related to this
> topic:
>
> 1. CUDA: performance portability with the Chapel language
>
> http://ieeexplore.ieee.org/document/6267860/?arnumber=6267860&tag=1
>
>
>
> 2. OpenCL: GPGPU Support in Chapel with the Radeon Open Compute Platform
>
>
>
> For the 1st work, I don't find the code in the trunk, how can I play
> with that? How does the compilation process actually work? (CUDA ith nvcc
> and C with gcc, then how to combine both and generate single binary)
>
>
>
> For 2nd, I don't find any detail except the limited information on the
> slides. Is that open source and available on Chapel what version? And what
> I need to play with it on my own machine? or it has to be on ROCm?
>
>
>
> Besides, is there any way for either of the above two to generate LLVM IR
> for the GPU-aware Chapel code? (including the host and device code)
>
>
>
> Thanks
>
>
> --
>
> Best regards
>
>
> Hui Zhang
>
--
Best regards
Hui Zhang
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