gpu_testing.jl

using CuArrays, FileIO, Colors, GPUArrays, BenchmarkTools, ImageShow
using CuArrays: CuArray
"""
The function calculating the Julia set
"""
function juliaset(z0, maxiter)
    c = ComplexF32(-0.5, 0.75)
    z = z0
    for i in 1:maxiter
        abs2(z) > 4f0 && return (i - 1) % UInt8
        z = z * z + c
    end
    return maxiter % UInt8 # % is used to convert without overflow check
end
range = 100:50:2^12
cutimes, jltimes = Float64[], Float64[]
function run_bench(in, out)
  # use dot syntax to apply `juliaset` to each elemt of q_converted
  # and write the output to result
  out .= juliaset.(in, 16)
  # all calls to the GPU are scheduled asynchronous,
  # so we need to synchronize
  GPUArrays.synchronize(out)
end
# store a reference to the last results for plotting
last_jl, last_cu = nothing, nothing
for N in range
  w, h = N, N
  q = [ComplexF32(r, i) for i=1:-(2.0/w):-1, r=-1.5:(3.0/h):1.5]
  for (times, Typ) in ((cutimes, CuArray), (jltimes, Array))
    # convert to Array or CuArray - moving the calculation to CPU/GPU
    q_converted = Typ(q)
    result = Typ(zeros(UInt8, size(q)))
    for i in 1:10 # 5 samples per size
      # benchmarking macro, all variables need to be prefixed with $
      t = Base.@elapsed begin
				run_bench(q_converted, result)
      end
      global last_jl, last_cu # we're in local scope
      if result isa CuArray
        last_cu = result
      else
      	last_jl = result
      end
      push!(times, t)
    end
  end
end

cu_jl = hcat(Array(last_cu), last_jl)
cmap = colormap("Blues", 16 + 1)
color_lookup(val, cmap) = cmap[val + 1]
color_lookup.(cu_jl, (cmap,))