A_mul_B!(Y, A, B) -> Y
Calculates the matrix-matrix or matrix-vector product A⋅B and stores the
result in Y, overwriting the
existing value of Y. Note that Y must not be aliased with either A or B.
julia> A=[1.0 2.0; 3.0 4.0]; B=[1.0 1.0; 1.0 1.0]; Y = similar(B);
A_mul_B!(Y, A, B);
julia> Y
2×2 Array{Float64,2}:
3.0 3.0
7.0 7.0
On Tue, Oct 18, 2016 at 10:27 AM, <[email protected]> wrote:
> hi guys
> is there a way to reduce allocated memory in matrix multiplications?
>
> for example this code blew in my machine gives :
>
> function test4(n)
> a = rand(n,n)
> for i = 1:100
> a*a
> end
> end
>
>
> ---------------------- answer ----------------------
> test4(1)
> # force compiling
>
> @time test4(1000)
> 16.589743 seconds (433 allocations: 770.587 MB, 0.68% gc time)
>
