Comments (5)
I seem to have made some change and am now unable to reproduce the error. I guess I will be closing this issue since I can't figure out what caused the error in the first place.
from metal.jl.
Can you post the actual error message? It's unclear what part of the toolchain is failing here.
Also, do you have an MWE?
from metal.jl.
I get this error message:
ERROR: Compilation to native code failed; see below for details.
If you think this is a bug, please file an issue and attach /var/folders/69/qsgfh7hj7csg_x4f7kcm2p9r0000gq/T/jl_JwhY1QBopO.metallib.
Stacktrace:
[1] error(s::String)
@ Base ./error.jl:35
[2] link(job::GPUCompiler.CompilerJob, compiled::NamedTuple{(:image, :entry), Tuple{Vector{UInt8}, String}}; return_function::Bool)
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/compilation.jl:78
[3] link(job::GPUCompiler.CompilerJob, compiled::NamedTuple{(:image, :entry), Tuple{Vector{UInt8}, String}})
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/compilation.jl:65
[4] actual_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, world::UInt64, cfg::GPUCompiler.CompilerConfig{GPUCompiler.MetalCompilerTarget, Metal.MetalCompilerParams}, compiler::typeof(Metal.compile), linker::typeof(Metal.link))
@ GPUCompiler ~/.julia/packages/GPUCompiler/U36Ed/src/execution.jl:132
[5] cached_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, cfg::GPUCompiler.CompilerConfig{GPUCompiler.MetalCompilerTarget, Metal.MetalCompilerParams}, compiler::Function, linker::Function)
@ GPUCompiler ~/.julia/packages/GPUCompiler/U36Ed/src/execution.jl:103
[6] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:185 [inlined]
[7] macro expansion
@ ./lock.jl:267 [inlined]
[8] mtlfunction(f::GPUArrays.var"#broadcast_kernel#38", tt::Type{Tuple{Metal.mtlKernelContext, MtlDeviceMatrix{Float32, 1}, Base.Broadcast.Broadcasted{Metal.MtlArrayStyle{2, Metal.MTL.MTLResourceStorageModePrivate}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Krang.ElectronSynchrotronPowerLawIntensity, Tuple{Base.Broadcast.Extruded{MtlDeviceMatrix{Krang.IntensityPixel{Float32}, 1}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}, Metal.MtlRefValue{Krang.UnionGeometry{Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}, Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}}}}}, Int64}}; name::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:180
[9] mtlfunction
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:178 [inlined]
[10] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:85 [inlined]
[11] #launch_heuristic#96
@ ~/.julia/packages/Metal/OchAS/src/gpuarrays.jl:14 [inlined]
[12] launch_heuristic
@ ~/.julia/packages/Metal/OchAS/src/gpuarrays.jl:12 [inlined]
[13] _copyto!
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:56 [inlined]
[14] copyto!
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:37 [inlined]
[15] copy
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:28 [inlined]
[16] materialize(bc::Base.Broadcast.Broadcasted{Metal.MtlArrayStyle{2, Metal.MTL.MTLResourceStorageModePrivate}, Nothing, Krang.ElectronSynchrotronPowerLawIntensity, Tuple{MtlMatrix{Krang.IntensityPixel{Float32}, Metal.MTL.MTLResourceStorageModePrivate}, Base.RefValue{Krang.UnionGeometry{Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}, Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}}}}})
@ Base.Broadcast ./broadcast.jl:873
[17] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/utilities.jl:10 [inlined]
[18] top-level scope
@ ~/.julia/packages/Metal/OchAS/src/pool.jl:175 [inlined]
[19] top-level scope
@ ~/Software/Krang.jl/examples/gpuexample.jl:0
caused by: NSError: Undefined symbols:
_julia_asn_3237, referenced from: _Z16broadcast_kernel16mtlKernelContext14MtlDeviceArrayI7Float32Li2ELi1EE11BroadcastedI13MtlArrayStyleILi2E39Metal_MTL_MTLResourceStorageModePrivateE5TupleI5OneToI5Int64ES5_IS6_EE36ElectronSynchrotronPowerLawIntensityS4_I8ExtrudedIS0_I14IntensityPixelIS1_ELi2ELi1EES4_I4BoolS10_ES4_IS6_S6_EE11MtlRefValueI13UnionGeometryI12ConeGeometryIS1_S4_I6SArrayIS4_ILi3EES1_Li1ELi3EES14_IS4_ILi3EES1_Li1ELi3EES4_IS6_S6_S6_E7profileS1_S1_EES13_IS1_S4_IS14_IS4_ILi3EES1_Li1ELi3EES14_IS4_ILi3EES1_Li1ELi3EES4_IS6_S6_S6_ES15_S1_S1_EEEEEES6_
_julia_asn_3237, referenced from: _Z16broadcast_kernel16mtlKernelContext14MtlDeviceArrayI7Float32Li2ELi1EE11BroadcastedI13MtlArrayStyleILi2E39Metal_MTL_MTLResourceStorageModePrivateE5TupleI5OneToI5Int64ES5_IS6_EE36ElectronSynchrotronPowerLawIntensityS4_I8ExtrudedIS0_I14IntensityPixelIS1_ELi2ELi1EES4_I4BoolS10_ES4_IS6_S6_EE11MtlRefValueI13UnionGeometryI12ConeGeometryIS1_S4_I6SArrayIS4_ILi3EES1_Li1ELi3EES14_IS4_ILi3EES1_Li1ELi3EES4_IS6_S6_S6_E7profileS1_S1_EES13_IS1_S4_IS14_IS4_ILi3EES1_Li1ELi3EES14_IS4_ILi3EES1_Li1ELi3EES4_IS6_S6_S6_ES15_S1_S1_EEEEEES6_
(AGXMetalG13X, code 2)
Stacktrace:
[1] MTLComputePipelineState(dev::Metal.MTL.MTLDeviceInstance, fun::Metal.MTL.MTLFunctionInstance)
@ Metal.MTL ~/.julia/packages/Metal/OchAS/lib/mtl/compute_pipeline.jl:60
[2] link(job::GPUCompiler.CompilerJob, compiled::NamedTuple{(:image, :entry), Tuple{Vector{UInt8}, String}}; return_function::Bool)
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/compilation.jl:70
[3] link(job::GPUCompiler.CompilerJob, compiled::NamedTuple{(:image, :entry), Tuple{Vector{UInt8}, String}})
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/compilation.jl:65
[4] actual_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, world::UInt64, cfg::GPUCompiler.CompilerConfig{GPUCompiler.MetalCompilerTarget, Metal.MetalCompilerParams}, compiler::typeof(Metal.compile), linker::typeof(Metal.link))
@ GPUCompiler ~/.julia/packages/GPUCompiler/U36Ed/src/execution.jl:132
[5] cached_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, cfg::GPUCompiler.CompilerConfig{GPUCompiler.MetalCompilerTarget, Metal.MetalCompilerParams}, compiler::Function, linker::Function)
@ GPUCompiler ~/.julia/packages/GPUCompiler/U36Ed/src/execution.jl:103
[6] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:185 [inlined]
[7] macro expansion
@ ./lock.jl:267 [inlined]
[8] mtlfunction(f::GPUArrays.var"#broadcast_kernel#38", tt::Type{Tuple{Metal.mtlKernelContext, MtlDeviceMatrix{Float32, 1}, Base.Broadcast.Broadcasted{Metal.MtlArrayStyle{2, Metal.MTL.MTLResourceStorageModePrivate}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Krang.ElectronSynchrotronPowerLawIntensity, Tuple{Base.Broadcast.Extruded{MtlDeviceMatrix{Krang.IntensityPixel{Float32}, 1}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}, Metal.MtlRefValue{Krang.UnionGeometry{Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}, Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}}}}}, Int64}}; name::Nothing, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ Metal ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:180
[9] mtlfunction
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:178 [inlined]
[10] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/compiler/execution.jl:85 [inlined]
[11] #launch_heuristic#96
@ ~/.julia/packages/Metal/OchAS/src/gpuarrays.jl:14 [inlined]
[12] launch_heuristic
@ ~/.julia/packages/Metal/OchAS/src/gpuarrays.jl:12 [inlined]
[13] _copyto!
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:56 [inlined]
[14] copyto!
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:37 [inlined]
[15] copy
@ ~/.julia/packages/GPUArrays/Hd5Sk/src/host/broadcast.jl:28 [inlined]
[16] materialize(bc::Base.Broadcast.Broadcasted{Metal.MtlArrayStyle{2, Metal.MTL.MTLResourceStorageModePrivate}, Nothing, Krang.ElectronSynchrotronPowerLawIntensity, Tuple{MtlMatrix{Krang.IntensityPixel{Float32}, Metal.MTL.MTLResourceStorageModePrivate}, Base.RefValue{Krang.UnionGeometry{Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}, Krang.ConeGeometry{Float32, Tuple{StaticArraysCore.SVector{3, Float32}, StaticArraysCore.SVector{3, Float32}, Tuple{Int64, Int64, Int64}, typeof(profile), Float32, Float32}}}}}})
@ Base.Broadcast ./broadcast.jl:873
[17] macro expansion
@ ~/.julia/packages/Metal/OchAS/src/utilities.jl:10 [inlined]
[18] top-level scope
@ ~/.julia/packages/Metal/OchAS/src/pool.jl:175 [inlined]
[19] top-level scope
@ ~/Software/Krang.jl/examples/gpuexample.jl:0
I'll work on seeing if I can produce a MWE
from metal.jl.
I think I found the heart of the error. It arrises whenever an array is constructed to be looped over in the function definition. So this causes an error:
arr = MtlArray(zeros(Float32, sze, sze))
function test(pix)
ans = 0f0
for n in [0,1,2]
ans += 1f0
end
return sum
end
test.(arr)
while this does not,
arr = MtlArray(zeros(Float32, sze, sze))
function test(pix)
ans = 0f0
for n in 0:2
ans += 1f0
end
return sum
end
test.(arr)
from metal.jl.
I think I found the heart of the error. It arrises whenever an array is constructed to be looped over in the function definition. So this causes an error:
for n in [0,1,2]
You're allocating a CPU array in there, which is unsupported, as the error message tells you:
julia> test.(arr)
ERROR: InvalidIRError: compiling MethodInstance for (::GPUArrays.var"#broadcast_kernel#38")(::Metal.mtlKernelContext, ::MtlDeviceMatrix{typeof(sum), 1}, ::Base.Broadcast.Broadcasted{Metal.MtlArrayStyle{2, Metal.MTL.MTLResourceStorageModePrivate}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, typeof(test), Tuple{Base.Broadcast.Extruded{MtlDeviceMatrix{Float32, 1}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}}}, ::Int64) resulted in invalid LLVM IR
Reason: unsupported call through a literal pointer (call to ijl_alloc_array_1d)
Stacktrace:
[1] Array
@ ./boot.jl:477
[2] Array
@ ./boot.jl:486
[3] similar
@ ./abstractarray.jl:884
[4] similar
@ ./abstractarray.jl:883
[5] _array_for
@ ./array.jl:671
[6] _array_for
@ ./array.jl:674
[7] vect
@ ./array.jl:126
[8] test
@ ./REPL[5]:3
[9] _broadcast_getindex_evalf
@ ./broadcast.jl:683
[10] _broadcast_getindex
@ ./broadcast.jl:656
[11] getindex
@ ./broadcast.jl:610
[12] broadcast_kernel
@ ~/.julia/packages/GPUArrays/EoKy0/src/host/broadcast.jl:59
Are you sure you've correctly reduced the error? The Compilation to native code failed
issue you originally reported is something we need to fix, but the InvalidIRError
your MWE throws is your problem.
Also please report the output of Metal.versioninfo()
from metal.jl.
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from metal.jl.