sparse_mat_vec.jl

results.jl

> a, b = bench(100_000, Float64, Int64)
(Trial(704.422 μs), Trial(1.505 ms)) # Julia 0.6
(Trial(1.354 ms), Trial(735.759 μs)) # Julia 0.7

sparse_mat_vec.jl

using Ranges, BenchmarkTools

function my_mul!(y::AbstractVector{Tv}, A::SparseMatrixCSC{Tv,Ti}, x::AbstractVector{Tv}) where {Tv,Ti}
    fill!(y, zero(Tv))

    @inbounds for i = RightOpen(1, A.n + 1)
        xval = x[i]
        for j = RightOpen(A.colptr[i], A.colptr[i+1])
            y[A.rowval[j]] += A.nzval[j] * xval
        end
    end
    y
end

function old_mul!(y::AbstractVector{Tv}, A::SparseMatrixCSC{Tv,Ti}, x::AbstractVector{Tv}) where {Tv,Ti}
    fill!(y, zero(Tv))

    @inbounds for i = 1 : A.n
        xval = x[i]
        for j = A.colptr[i] : A.colptr[i+1] - 1
            y[A.rowval[j]] += A.nzval[j] * xval
        end
    end
    y
end

function bench(n = 100_000, ::Type{Tv} = Float64, ::Type{Ti} = Int64) where {Tv,Ti}
    mat = spdiagm((fill(-1.0, n - 1), fill(2.0, n), fill(-1.2, n - 1),), (-1, 0, 1))
    A = convert(SparseMatrixCSC{Tv,Ti}, mat)
    x = rand(Tv, n)
    y = similar(x)

    fst = @benchmark my_mul!($y, $A, $x)
    snd = @benchmark old_mul!($y, $A, $x)

    fst, snd
end