ProfileCanvas

This package is intended as a drop-in replacement for ProfileView.jl and ProfileSVG.jl.

It exposes the HTML canvas based profile viewer UI used by the Julia extension for VS Code in the REPL and environments that can display HTML (like Pluto notebooks). Performance should be significantly better than SVG-based solutions, especially for very large traces.

using ProfileCanvas
function profile_test(n)
    for i = 1:n
        A = randn(100,100,20)
        m = maximum(A)
        Am = mapslices(sum, A; dims=2)
        B = A[:,:,5]
        Bsort = mapslices(sort, B; dims=1)
        b = rand(100)
        C = B.*b
    end
end

@profview profile_test(1)  # run once to trigger compilation (ignore this one)
@profview profile_test(10)

On Julia 1.8 and newer you can also use profiler memory allocations with @profview_allocs/view_allocs:

@profview_allocs profile_test(10)

The controls are mouse wheel to scroll, and click on a cell to base the zoom on it. The end result depends on the julia version, but it might be something like this:

when run from the REPL and

in a Pluto notebook.

The profiling data is color-coded to provide insights about the performance of your code:

• Red bars represent function calls resolved at run-time, which often have a significant impact on performance. While some red is unavoidable, excessive red may indicate a performance bottleneck.
• Yellow bars indicate a site of garbage collection, which is often triggered by memory allocation. These sites can often be optimized by reducing the amount of temporary memory allocated by your code.