Introduction to GPU Programming in Chapel

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  • chapel

    a Productive Parallel Programming Language

  • Thanks, @subharmonicon!

    While Chapel can run on many different systems, the main goal is making HPC programming much easier. Therefore, we are currently focusing on hardware that you can find in HPC systems (NVIDIA, AMD and Intel). Metal doesn't fall into that category, unfortunately. So far, the name came up infrequently in our discussions IIRC (especially targetting SPIRV), but we haven't heard from any [potential] user who may be interested in it. I would encourage you or anybody else interested in it to create an issue asking for the feature: https://github.com/chapel-lang/chapel/issues/new. Seeing public interest in that direction can change our prioritization.

    One thing that I wanted to add that's not in the blogpost is the "cpu-as-device" mode. With that mode, you can use any machine, even one without a GPU, to write applications using Chapel's GPU features. That mode is for those who want to do initial development/debugging on their personal laptops before putting their application on an HPC system. In other words, while you can't use Metal directly, you can still write GPU-enabled applications in your Mac using Chapel, if the end goal is to run it on an HPC system. More details on cpu-as-device: https://chapel-lang.org/docs/main/technotes/gpu.html#cpu-as-...

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