support emitting a generated function

[vchuravy]

Motivated by #665

Proposed syntax

@kernel generated=true function f(::Val{N}) where N
           KernelAbstractions.Extras.@unroll $N for i in 1:10
           end
       end

Sadly this doesn't quite work yet, since I need to handle the $N correctly

Currently:

    function cpu_f(__ctx__, ::Val{N}; ) where N
        if $(Expr(:generated))
            $(Expr(:copyast, :($(QuoteNode(:(let
      begin
          var"##N#249" = length((KernelAbstractions.__workitems_iterspace)(__ctx__))
          begin
              #= /home/vchuravy/src/KernelAbstractions/src/macros.jl:317 =#
              for var"##I#248" = (KernelAbstractions.__workitems_iterspace)(__ctx__)
                  #= /home/vchuravy/src/KernelAbstractions/src/macros.jl:318 =#
                  (KernelAbstractions.__validindex)(__ctx__, var"##I#248") || continue
                  #= /home/vchuravy/src/KernelAbstractions/src/macros.jl:319 =#
                  #= /home/vchuravy/src/KernelAbstractions/src/macros.jl:320 =#
                  #= REPL[19]:2 =# KernelAbstractions.Extra.@unroll $(Expr(:$, :N)) for i = 1:10
                          #= REPL[19]:2 =#
                          #= REPL[19]:3 =#
                      end
                  #= /home/vchuravy/src/KernelAbstractions/src/macros.jl:321 =#
              end
          end
      end
      return nothing
  end))))))
        else
            $(Expr(:meta, :generated_only))
        end
    end

Whereas

julia> @macroexpand @generated function(::Val{N}) where N
           quote
               KernelAbstractions.Extras.@unroll $N for i in 1:10
               end
           end
       end
:(function (::Val{N},) where N
      #= REPL[18]:1 =#
      if $(Expr(:generated))
          #= REPL[18]:1 =#
          #= REPL[18]:2 =#
          Core._expr(:block, $(QuoteNode(:(#= REPL[18]:3 =#))), Core._expr(:macrocall, $(Expr(:copyast, :($(QuoteNode(:(KernelAbstractions.Extras.var"@unroll")))))), $(QuoteNode(:(#= REPL[18]:3 =#))), N, $(Expr(:copyast, :($(QuoteNode(:(for i = 1:10
      #= REPL[18]:3 =#
      #= REPL[18]:4 =#
  end))))))))
      else
          $(Expr(:meta, :generated_only))
          return
      end
  end)

Note that the QuoteNode got broken into smaller pieces with the interpolated variable being left alone and the rest being passed to _expr and QuoteNode

[github-actions]

Benchmark Results

	main	d4ffa3b...	main / d4ffa3b...
saxpy/default/Float32/1024	0.0728 ± 0.029 ms	0.627 ± 0.0079 μs	116 ± 46
saxpy/default/Float32/1048576	0.454 ± 0.022 ms	0.274 ± 0.02 ms	1.65 ± 0.14
saxpy/default/Float32/16384	0.0702 ± 0.03 ms	2.84 ± 0.31 μs	24.7 ± 11
saxpy/default/Float32/2048	0.0737 ± 0.03 ms	0.76 ± 0.059 μs	96.9 ± 40
saxpy/default/Float32/256	0.0721 ± 0.028 ms	0.565 ± 0.0053 μs	128 ± 49
saxpy/default/Float32/262144	0.167 ± 0.029 ms	0.0676 ± 0.0046 ms	2.47 ± 0.47
saxpy/default/Float32/32768	0.0713 ± 0.03 ms	5.49 ± 0.59 μs	13 ± 5.7
saxpy/default/Float32/4096	0.0755 ± 0.031 ms	1.13 ± 0.14 μs	66.6 ± 28
saxpy/default/Float32/512	0.0711 ± 0.029 ms	0.598 ± 0.0056 μs	119 ± 49
saxpy/default/Float32/64	0.0721 ± 0.029 ms	0.555 ± 0.0052 μs	130 ± 51
saxpy/default/Float32/65536	0.0938 ± 0.03 ms	13.8 ± 1.1 μs	6.77 ± 2.2
saxpy/default/Float64/1024	0.0689 ± 0.03 ms	0.746 ± 0.046 μs	92.3 ± 41
saxpy/default/Float64/1048576	0.615 ± 0.099 ms	0.595 ± 0.052 ms	1.03 ± 0.19
saxpy/default/Float64/16384	0.0773 ± 0.03 ms	5.45 ± 0.5 μs	14.2 ± 5.6
saxpy/default/Float64/2048	0.0697 ± 0.029 ms	1.17 ± 0.15 μs	59.7 ± 26
saxpy/default/Float64/256	0.0637 ± 0.031 ms	0.58 ± 0.0071 μs	110 ± 53
saxpy/default/Float64/262144	0.196 ± 0.034 ms	0.135 ± 0.013 ms	1.45 ± 0.29
saxpy/default/Float64/32768	0.0844 ± 0.029 ms	13.8 ± 1.1 μs	6.1 ± 2.1
saxpy/default/Float64/4096	0.071 ± 0.03 ms	1.73 ± 0.2 μs	41 ± 18
saxpy/default/Float64/512	0.0688 ± 0.03 ms	0.634 ± 0.0093 μs	108 ± 47
saxpy/default/Float64/64	0.0653 ± 0.031 ms	0.554 ± 0.0069 μs	118 ± 57
saxpy/default/Float64/65536	0.104 ± 0.03 ms	0.0334 ± 0.0024 ms	3.11 ± 0.92
saxpy/static workgroup=(1024,)/Float32/1024	0.0706 ± 0.029 ms	2.06 ± 0.026 μs	34.3 ± 14
saxpy/static workgroup=(1024,)/Float32/1048576	0.457 ± 0.023 ms	0.281 ± 0.022 ms	1.63 ± 0.15
saxpy/static workgroup=(1024,)/Float32/16384	0.0679 ± 0.029 ms	4.33 ± 0.34 μs	15.7 ± 6.8
saxpy/static workgroup=(1024,)/Float32/2048	0.0659 ± 0.029 ms	2.22 ± 0.083 μs	29.7 ± 13
saxpy/static workgroup=(1024,)/Float32/256	0.0696 ± 0.029 ms	2.55 ± 0.022 μs	27.3 ± 11
saxpy/static workgroup=(1024,)/Float32/262144	0.165 ± 0.028 ms	0.0693 ± 0.013 ms	2.39 ± 0.6
saxpy/static workgroup=(1024,)/Float32/32768	0.0759 ± 0.03 ms	7.67 ± 0.64 μs	9.89 ± 4.1
saxpy/static workgroup=(1024,)/Float32/4096	0.0725 ± 0.031 ms	2.56 ± 0.13 μs	28.3 ± 12
saxpy/static workgroup=(1024,)/Float32/512	0.0704 ± 0.029 ms	2.7 ± 0.027 μs	26.1 ± 11
saxpy/static workgroup=(1024,)/Float32/64	0.0683 ± 0.03 ms	2.45 ± 0.021 μs	27.9 ± 12
saxpy/static workgroup=(1024,)/Float32/65536	0.0897 ± 0.031 ms	17 ± 2.3 μs	5.29 ± 2
saxpy/static workgroup=(1024,)/Float64/1024	0.0681 ± 0.029 ms	2.23 ± 0.075 μs	30.6 ± 13
saxpy/static workgroup=(1024,)/Float64/1048576	0.576 ± 0.077 ms	0.649 ± 0.11 ms	0.887 ± 0.19
saxpy/static workgroup=(1024,)/Float64/16384	0.0754 ± 0.029 ms	7.64 ± 0.66 μs	9.87 ± 3.9
saxpy/static workgroup=(1024,)/Float64/2048	0.0705 ± 0.03 ms	2.56 ± 0.13 μs	27.6 ± 12
saxpy/static workgroup=(1024,)/Float64/256	0.0656 ± 0.029 ms	2.55 ± 0.026 μs	25.7 ± 11
saxpy/static workgroup=(1024,)/Float64/262144	0.197 ± 0.031 ms	0.144 ± 0.025 ms	1.37 ± 0.32
saxpy/static workgroup=(1024,)/Float64/32768	0.0818 ± 0.028 ms	17.1 ± 1.8 μs	4.8 ± 1.7
saxpy/static workgroup=(1024,)/Float64/4096	0.071 ± 0.03 ms	3.11 ± 0.21 μs	22.8 ± 9.8
saxpy/static workgroup=(1024,)/Float64/512	0.0695 ± 0.029 ms	2.71 ± 0.031 μs	25.6 ± 11
saxpy/static workgroup=(1024,)/Float64/64	0.0682 ± 0.03 ms	2.43 ± 0.021 μs	28.1 ± 12
saxpy/static workgroup=(1024,)/Float64/65536	0.102 ± 0.031 ms	0.0362 ± 0.0054 ms	2.81 ± 0.95
time_to_load	1.01 ± 0.036 s	0.298 ± 0.0018 s	3.4 ± 0.12

Benchmark Plots

A plot of the benchmark results have been uploaded as an artifact to the workflow run for this PR.
Go to "Actions"->"Benchmark a pull request"->[the most recent run]->"Artifacts" (at the bottom).

[codecov]

Codecov Report

❌ Patch coverage is 46.15385% with 7 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.36%. Comparing base (1f84b17) to head (9195d94).

Files with missing lines	Patch %	Lines
src/macros.jl	42.85%	4 Missing ⚠️
src/KernelAbstractions.jl	50.00%	3 Missing ⚠️

Additional details and impacted files

@@               Coverage Diff               @@
##           release-0.9     #667      +/-   ##
===============================================
- Coverage        71.85%   71.36%   -0.49%     
===============================================
  Files               14       14              
  Lines              906      915       +9     
===============================================
+ Hits               651      653       +2     
- Misses             255      262       +7     

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[vchuravy]

julia> @kernel generated=false function g(::Val{N}) where N
                  KernelAbstractions.Extras.@unroll $N for i in 1:10
                  end
              end
ERROR: LoadError: Syntax error: `@unroll N expr` needs a constant integer N
Stacktrace:
 [1] error(s::String)
   @ Base ./error.jl:35
 [2] var"@unroll"(__source__::LineNumberNode, __module__::Module, N::Any, expr::Any)
   @ KernelAbstractions.Extras.LoopInfo ~/src/KernelAbstractions/src/extras/loopinfo.jl:60
in expression starting at REPL[5]:2

julia> @kernel generated=true function f(::Val{N}) where N
                  KernelAbstractions.Extras.@unroll $N for i in 1:10
                  end
              end

 @ka_code_llvm optimize=false raw=true dump_module = true f(CPU())(Val(17), ndrange=1)

; ...
L33:                                              ; preds = %L29
; │ @ none within `macro expansion` @ /home/vchuravy/src/KernelAbstractions/src/macros.jl:321
; │┌ @ multidimensional.jl:417 within `iterate`
    br label %L22, !dbg !87, !llvm.loop !100
; ...
!100 = distinct !{!100, !101}
!101 = !{!"llvm.loop.unroll.count", i64 17}

Seems to work!

[vchuravy]

Homework for myself:

Write the kernel below with @nif

f(x::Integer) = 1
f(x::AbstractFloat) = 2

@kernel function _kern!(A::AbstractArray, B::AbstractArray)
    idx = @index(Global, Cartesian) 
    tpl = B[idx]
    k = tpl[1] > 0 ? 2 : 1
    A[idx] = ntuple(Val(length(tpl))) do j
        if j == k
            f(tpl[j])
        end
    end[k]
    nothing
end

wtf(N=64) = let
    A = cu(zeros(N,N))
    B = cu(tuple.(randn(N,N), ones(Int,N,N)))
    _kern!(get_backend(A))(A, B; ndrange=size(A))
end