Broadcasted multiplication with a rational doesn't work

[bicycle1885]

Broadcasted multiplication with a rational number and a CUDA array doesn't work if its wrapped in a function. I've tested this on the latest release and the master branch.

The Minimal Working Example (MWE) for this bug:

julia> using CUDA

julia> f(x) = 2//3 * x
f (generic function with 1 method)

julia> x = cu(randn(Float32, 3))
3-element CuArray{Float32, 1, CUDA.Mem.DeviceBuffer}:
 -1.3022956
  1.2664111
 -2.5245302

julia> 2//3 .* x  # OK
3-element CuArray{Float32, 1, CUDA.Mem.DeviceBuffer}:
 -0.8681971
  0.84427404
 -1.6830201

julia> f.(x)  # This doesn't work
ERROR: InvalidIRError: compiling MethodInstance for (::GPUArrays.var"#broadcast_kernel#28")(::CUDA.CuKernelContext, ::CuDeviceVector{Float32, 1}, ::Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(f), Tuple{Base.Broadcast.Extruded{CuDeviceVector{Float32, 1}, Tuple{Bool}, Tuple{Int64}}}}, ::Int64) resulted in invalid LLVM IR
Reason: unsupported dynamic function invocation (call to __throw_rational_argerror_typemin(T) @ Base rational.jl:20)
Stacktrace:
 [1] checked_den
   @ ./rational.jl:24
 [2] Rational
   @ ./rational.jl:36
 [3] Rational
   @ ./rational.jl:39
 [4] //
   @ ./rational.jl:62
 [5] f
   @ ./REPL[3]:1
 [6] _broadcast_getindex_evalf
   @ ./broadcast.jl:683
 [7] _broadcast_getindex
   @ ./broadcast.jl:656
 [8] getindex
   @ ./broadcast.jl:610
 [9] broadcast_kernel
   @ ~/.julia/packages/GPUArrays/TnEpb/src/host/broadcast.jl:59
Hint: catch this exception as `err` and call `code_typed(err; interactive = true)` to introspect the erronous code with Cthulhu.jl
Stacktrace:
  [1] check_ir(job::GPUCompiler.CompilerJob{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}, args::LLVM.Module)
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/validation.jl:154
  [2] macro expansion
    @ ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:407 [inlined]
  [3] macro expansion
    @ ~/.julia/packages/TimerOutputs/RsWnF/src/TimerOutput.jl:253 [inlined]
  [4] macro expansion
    @ ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:406 [inlined]
  [5] emit_llvm(job::GPUCompiler.CompilerJob; libraries::Bool, deferred_codegen::Bool, optimize::Bool, cleanup::Bool, only_entry::Bool, validate::Bool, ctx::LLVM.ThreadSafeContext)
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/utils.jl:89
  [6] codegen(output::Symbol, job::GPUCompiler.CompilerJob; libraries::Bool, deferred_codegen::Bool, optimize::Bool, cleanup::Bool, strip::Bool, validate::Bool, only_entry::Bool, parent_job::Nothing, ctx::LLVM.ThreadSafeContext)
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:120
  [7] codegen
    @ ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:94 [inlined]
  [8] compile(target::Symbol, job::GPUCompiler.CompilerJob; libraries::Bool, deferred_codegen::Bool, optimize::Bool, cleanup::Bool, strip::Bool, validate::Bool, only_entry::Bool, ctx::LLVM.ThreadSafeContext)
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:90
  [9] compile
    @ ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:81 [inlined]
 [10] compile(job::GPUCompiler.CompilerJob, ctx::LLVM.ThreadSafeContext)
    @ CUDA ~/.julia/packages/CUDA/HzJ3E/src/compiler/compilation.jl:105
 [11] #1033
    @ ~/.julia/packages/CUDA/HzJ3E/src/compiler/compilation.jl:100 [inlined]
 [12] LLVM.ThreadSafeContext(f::CUDA.var"#1033#1034"{GPUCompiler.CompilerJob{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}})
    @ LLVM ~/.julia/packages/LLVM/bsdku/src/executionengine/ts_module.jl:14
 [13] JuliaContext
    @ ~/.julia/packages/GPUCompiler/gY1vE/src/driver.jl:35 [inlined]
 [14] compile
    @ ~/.julia/packages/CUDA/HzJ3E/src/compiler/compilation.jl:99 [inlined]
 [15] actual_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, world::UInt64, cfg::GPUCompiler.CompilerConfig{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}, compiler::typeof(CUDA.compile), linker::typeof(CUDA.link))
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/execution.jl:125
 [16] cached_compilation(cache::Dict{Any, Any}, src::Core.MethodInstance, cfg::GPUCompiler.CompilerConfig{GPUCompiler.PTXCompilerTarget, CUDA.CUDACompilerParams}, compiler::Function, linker::Function)
    @ GPUCompiler ~/.julia/packages/GPUCompiler/gY1vE/src/execution.jl:103
 [17] macro expansion
    @ ~/.julia/packages/CUDA/HzJ3E/src/compiler/execution.jl:311 [inlined]
 [18] macro expansion
    @ ./lock.jl:267 [inlined]
 [19] cufunction(f::GPUArrays.var"#broadcast_kernel#28", tt::Type{Tuple{CUDA.CuKernelContext, CuDeviceVector{Float32, 1}, Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Tuple{Base.OneTo{Int64}}, typeof(f), Tuple{Base.Broadcast.Extruded{CuDeviceVector{Float32, 1}, Tuple{Bool}, Tuple{Int64}}}}, Int64}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ CUDA ~/.julia/packages/CUDA/HzJ3E/src/compiler/execution.jl:306
 [20] cufunction
    @ ~/.julia/packages/CUDA/HzJ3E/src/compiler/execution.jl:303 [inlined]
 [21] macro expansion
    @ ~/.julia/packages/CUDA/HzJ3E/src/compiler/execution.jl:104 [inlined]
 [22] #launch_heuristic#1074
    @ ~/.julia/packages/CUDA/HzJ3E/src/gpuarrays.jl:17 [inlined]
 [23] launch_heuristic
    @ ~/.julia/packages/CUDA/HzJ3E/src/gpuarrays.jl:15 [inlined]
 [24] _copyto!
    @ ~/.julia/packages/GPUArrays/TnEpb/src/host/broadcast.jl:65 [inlined]
 [25] copyto!
    @ ~/.julia/packages/GPUArrays/TnEpb/src/host/broadcast.jl:46 [inlined]
 [26] copy
    @ ~/.julia/packages/GPUArrays/TnEpb/src/host/broadcast.jl:37 [inlined]
 [27] materialize(bc::Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Nothing, typeof(f), Tuple{CuArray{Float32, 1, CUDA.Mem.DeviceBuffer}}})
    @ Base.Broadcast ./broadcast.jl:873
 [28] top-level scope
    @ REPL[6]:1
 [29] top-level scope
    @ ~/.julia/packages/CUDA/HzJ3E/src/initialization.jl:171

julia> versioninfo()
Julia Version 1.9.0
Commit 8e630552924 (2023-05-07 11:25 UTC)
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 36 × Intel(R) Core(TM) i9-10980XE CPU @ 3.00GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, cascadelake)
  Threads: 1 on 36 virtual cores
Environment:
  JULIA_PROJECT = @.

julia> CUDA.versioninfo()
CUDA runtime 12.1, artifact installation
CUDA driver 12.1
NVIDIA driver 510.108.3, originally for CUDA 11.6

CUDA libraries: 
- CUBLAS: 12.1.3
- CURAND: 10.3.2
- CUFFT: 11.0.2
- CUSOLVER: 11.4.5
- CUSPARSE: 12.1.0
- CUPTI: 18.0.0
- NVML: 11.0.0+510.108.3

Julia packages: 
- CUDA.jl: 4.3.0
- CUDA_Driver_jll: 0.5.0+1
- CUDA_Runtime_jll: 0.6.0+0
- CUDA_Runtime_Discovery: 0.2.2

Toolchain:
- Julia: 1.9.0
- LLVM: 14.0.6
- PTX ISA support: 3.2, 4.0, 4.1, 4.2, 4.3, 5.0, 6.0, 6.1, 6.3, 6.4, 6.5, 7.0, 7.1, 7.2, 7.3, 7.4, 7.5
- Device capability support: sm_37, sm_50, sm_52, sm_53, sm_60, sm_61, sm_62, sm_70, sm_72, sm_75, sm_80, sm_86

1 device:
  0: NVIDIA RTX A6000 (sm_86, 46.001 GiB / 47.988 GiB available)

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[maleadt]

That should just be a matter of adding a quirk to quirks.jl for __throw_rational_argerror_typemin.

[Jay-sanjay]

Hello sir, I would be happy to work on it,
for this we firstly need to define __throw_rational_argerror_typemin
where is it defined sir.......?