Comments (2)
As you mention the array API is supposed to be vendor neutral.
For kernel programming, we're aiming for https://github.com/JuliaGPU/KernelAbstractions.jl to be that neutral API. It currently has support for CUDA.jl, and is used by several projects, but its dependency on Cassette.jl is problematic (but we expect to be able to get rid of that in the future). Alternatively, GPUArrays.jl has a similar DSL for vendor-neutral kernels, but we hope to rebuild that on top of KernelAbstractions.jl as soon as possible.
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Thanks looks great, I'll try it out for prototyping!
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Related Issues (20)
- oneAPI.rand() creates a CPU array
- Memory leak when running GPU broadcast in a loop HOT 6
- Explore the unified runtime HOT 1
- KernelAbstractions: add Atomix back-end HOT 1
- FPGA support
- Support for Gen9 hardware regressed? HOT 2
- MKL upgrade breaks support library HOT 18
- oneMKL.hemv does not respect queue order HOT 1
- Intel Data Center GPU Max series is not supported? HOT 11
- Alchemist hardware HOT 1
- test results on ARC770 HOT 1
- Failed to initialize oneAPI HOT 1
- oneapi 2024.0 - make_queue native API prototype update HOT 1
- Error on Linux/NixOS (ENOENT on shared libaries) HOT 3
- oneMKL tests failing due to missing symbols in oneapi support library HOT 7
- Native Windows support
- oneAPI with nested integrals HOT 1
- Fail to import HOT 11
- When should we use __FORCE_MKL_FLUSH__ in the C interface? HOT 5
- PVC support HOT 13
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