[Openmp-dev] OpenMP offload implicitly using streams

[Finkel, Hal J. via Openmp-dev]

Thanks, Ye. I suppose that I thought it always worked that way :-)

Alexey, Doru, do you know if there's any semantic problem or other concerns with enabling this option and/or making it the default?

 -Hal

On 3/20/19 11:32 AM, Ye Luo via Openmp-dev wrote:
Hi all,
After going through the source, I didn't find CUDA stream support.
Luckily, I only need to add
#define CUDA_API_PER_THREAD_DEFAULT_STREAM
before
#include <cuda.h>
in libomptarget/plugins/cuda/src/rtl.cpp
Then the multiple target goes to different streams and may execute concurrently.
#pragma omp parallel
{
  #pragma omp target
  {
    //offload computation
  }
}
This is exactly I want.

I know the XL compiler uses streams in a different way but achieves similar effects.
Is there anyone working on using streams with openmp target in llvm?
Will clang-ykt get something similar to XL and upstream to the mainline?

If we just add #define CUDA_API_PER_THREAD_DEFAULT_STREAM in the cuda rtl, will it be a trouble?
As a compiler user, I'd like to have a better solution rather than having a patch just for myself.

Best,
Ye
===================
Ye Luo, Ph.D.
Computational Science Division & Leadership Computing Facility
Argonne National Laboratory


Ye Luo <xw111luoye at gmail.com<mailto:xw111luoye at gmail.com>> 于2019年3月17日周日 下午2:26写道：
Hi,
How to turn on streams when using OpenMP offload?
When different host threads individually start target regions (even not using nowait). The offloaded computation goes to different CUDA streams and may execute concurrently. This is currently available in XL.
With Clang, nvprof shows only the run only uses the default stream.
Is there a way to do that with Clang?
On the other hand,
nvcc has option --default-stream per-thread
I'm not familar with clang CUDA, is there a similar option?
Best,
Ye
===================
Ye Luo, Ph.D.
Computational Science Division & Leadership Computing Facility
Argonne National Laboratory



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--
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory
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