Memory allocation and solve linear systems in Julia

I'm using Julia 1.5.0. Consider the following code:

using LinearAlgebra
using Distributions
using BenchmarkTools

function solve_b!(A, tol_iters)
    b   = [1.0 2.0]'
    luA = lu!(A)
    x   = [0.0; 0.0]
    for i =1:tol_iters
        A[1,1] += 0.001
        A[2,2] += 0.001
        luA = lu!(A)
        ldiv!(x, luA, b)
    end
end

A = rand(2,2)
solve_b!(A, 1000)

If I run this with julia --track-allocation=user, I see that most of the memory allocation comes from b = [1.0 2.0]' and x = [0.0; 0.0]. That is, when I see the .mem file, I see the following:

   96     b   = [1.0 2.0]'
    0     luA = lu!(A)
   96     x   = [0.0; 0.0]

The memory allocation increases as I increase tol_iters. Can someone explain why? I'm using lu! and ldiv!, so I would expect the update to be in-place. Therefore there should not be any additional memory allocation associated with the number of iterations.