mandelbrot.jl

#= one can use these to test fastmath-like path in controlled way
@inline mul_fast(x::T, y::T) where {T<:Complex} =
        T(complex(muladd(-imag(x), imag(y), real(x)*real(y)),
                  muladd( real(x), imag(y), imag(x)*real(y))))

@inline abs2_fast(z::Complex) = muladd(real(z), real(z), imag(z)*imag(z))
=#

function run_julia(height, width)
    y = range(-1.0f0, 0.0f0; length = height)
    x = range(-1.5f0, 0.0f0; length = width)
    c = x' .+ y*im
    fractal = fill(Int32(20), height, width)
    @inbounds for w in 1:width
    for h in 1:height
            _c = c[h, w]
            z = _c
            for i in 1:20
                z = z^2 + _c
                if abs2(z) > 4
                    fractal[h, w] = i
                    break
                end
            end
        end
    end
    return fractal
end

julia> @benchmark run_julia(2000, 3000)
BenchmarkTools.Trial: 27 samples with 1 evaluation.
 Range (min … max):  181.366 ms … 222.897 ms  ┊ GC (min … max): 0.20% … 17.82%
 Time  (median):     182.620 ms               ┊ GC (median):    0.23%
 Time  (mean ± σ):   185.657 ms ±   9.775 ms  ┊ GC (mean ± σ):  1.78% ±  4.44%

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  ██▇▇▄▆▁▁▁▁▁▄▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▄▁▁▁▁▁▁▁▁▁▁▄ ▁
  181 ms           Histogram: frequency by time          223 ms <

 Memory estimate: 68.66 MiB, allocs estimate: 4.

julia> @benchmark run_julia(4000, 6000)
BenchmarkTools.Trial: 7 samples with 1 evaluation.
 Range (min … max):  728.765 ms … 773.615 ms  ┊ GC (min … max): 0.06% … 5.51%
 Time  (median):     731.186 ms               ┊ GC (median):    0.17%
 Time  (mean ± σ):   742.578 ms ±  18.685 ms  ┊ GC (mean ± σ):  1.73% ± 2.37%

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  ██▁█▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁█ ▁
  729 ms           Histogram: frequency by time          774 ms <

 Memory estimate: 274.66 MiB, allocs estimate: 4.

plot-mandelbrot-on-all-accelerators-colab.svg

plot-mandelbrot-on-all-accelerators.svg