preallocate actually has more (while not by number of bytes) allocations! #22
Description
FYI: I was looking into this package, and ran the code from the README, and (at least on Julia 1.5) it has two extra allocations.
[From the tag-line: "Remember what memory we needed last time and use it gain every time after", better to change to "to gain" and finish with a period?]
Since preallocation wasn't clearly (much) faster, I was thinking isn't that the point (and to have less/or not variability for real-time), maybe the timing wasn't reliable, so I checked:
julia> @btime f(A, B, C);
33.333 ms (4 allocations: 15.26 MiB)
julia> @btime preallocated_f(A, B, C);
27.981 ms (6 allocations: 272 bytes)
julia> @btime preallocated_f(A, B, C);
38.364 ms (6 allocations: 272 bytes)
julia> @btime preallocated_f(A, B, C);
21.913 ms (6 allocations: 272 bytes)
julia> @btime f(A, B, C);
22.533 ms (4 allocations: 15.26 MiB)
I guess this is also useful for GPUs, some such way needed there?
Is a better example needed to show the usefulness? FYI2, I tried with a larger arrays (and I think it mostly shows how fast/good Julia's GC is):
julia> A, B, C = (rand(10000, 10000) for _ in 1:3)
Base.Generator{UnitRange{Int64},var"#14#15"}(var"#14#15"(), 1:3)
[..]
julia> @btime f(A, B, C);
23.648 s (4 allocations: 1.49 GiB)
julia> @btime preallocated_f(A, B, C);
22.597 s (6 allocations: 272 bytes)
julia> @time preallocated_f(A, B, C);
22.931816 seconds (6 allocations: 272 bytes)
julia> @time f(A, B, C);
22.840137 seconds (4 allocations: 1.490 GiB)