Memory Allocation when using mul! with sparse arrays and views

[gdalle]

I think this might be the same as

Why does `mul!(u, A, v)` allocate when `A` is sparse and `u, v` are views?

I’m wondering if there is a way to avoid allocations in the following scenario: julia> using BenchmarkTools, LinearAlgebra, SparseArrays julia> A = sprand(2, 3, 0.5); julia> u, v = rand(2), rand(3); julia> @btime mul!($u, $A, $v); 21.139 ns (0 allocations: 0 bytes) julia> u, v = view(rand(2, 3), :, 1), view(rand(2, 3), 1, :); julia> @btime mul!($u, $A, $v); 33.731 ns (1 allocation: 48 bytes) If it helps, the size of the allocation does not increase with the size of the arrays

However, note that to benchmark functions properly, you need to use BenchmarkTools.jl and interpolate variables with a dollar sign. Otherwise your allocation count will be biased by the presence of global variables.