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I don't know about "clearly the way to go". I think Julia's parallelism models have proven themselves to be very robust, performant and composeable, moreso than

I don't know about "clearly the way to go". I think Julia's parallelism models have proven themselves to be very robust, performant and composeable, moreso than OpenMP as far as I'm aware.

The_rationalist 7y ago
How can I annotate an existing loop to offload it on the GPU Inclusive OR on AVX IOR on cpu cores. Without this ability, in practice I use far less parallelism.
- dagw 7y ago
  This is currently no official solution in Julia that I'm aware of. However there are several people working on it and a few experimental solution are under active development https://github.com/JuliaDiffEq/AutoOffload.jl https://github.com/JuliaDiffEq/AutoOffload.jl https://juliagpu.gitlab.io/GPUifyLoops.jl/ https://juliagpu.gitlab.io/GPUifyLoops.jl/
  - ChrisRackauckas 7y ago
    AutoOffload is something different, where it's trying to do linear algebra in a way that auto-offloads to GPUs or heterogeneous. GPUifyLoops is correct for this answer, and its next incarnation is KernelAbstractions.jl. These auto-construct GPU kernels and such from loops.