Comments (3)
Yeah, this is a known issue. Everything is a bit in flux right now :-) Try using #13 in combination with GPUCompiler#master. I'm currently in the process of stabilizing things, and hope to release something within the next couple of weeks.
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Still not working for me, but I'll keep an eye out and I appreciate the incredible work! Really excited for the future of SOCs
from metal.jl.
You aren't using GPUCompiler#master, as that error has been fixed there: https://github.com/JuliaGPU/GPUCompiler.jl/blob/96569b469afee52d0fdba2cab8d158ba9932b74a/src/metal.jl#L224=
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Related Issues (20)
- `fill!` for `Int8` errors when the value is negative
- Support for macOS Sonoma HOT 1
- Long stacktrace when trying to create Float64 rand arrays HOT 2
- allowscalar equivalent for Metal.jl HOT 2
- Equivalent of cuSparse - start with sparse matvec HOT 7
- MPS - Support for Convolutional Neural Network kernels
- sum(vector) allocates a lot and feels slow. HOT 2
- Better error message for mixing MtlArray and Array operations
- Compilation failure due to high register usage HOT 3
- Threadgroup atomics require all-atomic operation HOT 3
- KernelAbstractions: add Atomix back-end
- Define map! ? HOT 1
- Q: How to debug kernels - KA.@print?
- Crash during MTLDispatchListApply HOT 14
- Unable to compile trig functions through ForwardDiff HOT 4
- `symbol multiply defined!` Bug/crash on Julia master, fine on 1.10 HOT 1
- `log1p` fails on `MtlArray{Float32}` HOT 10
- When precompiling, UndefVarError: `CompilerConfig` not defined HOT 2
- Legalization errors with vectorized code HOT 3
- Use vkFFT for FFT support HOT 2
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