Why accelerated ordering by multiplying the vector matrices of Julia accelerated?

Question

Why accelerated ordering by multiplying the vector matrices of Julia accelerated?

I have tried the following.

a = randn(100,100);
b = randn(100,100);
c = randn(100,1);

@time a*b*c
@time a*(b*c)

results

julia> @time abc; 0.000591 seconds (7 distributions: 79.234 KiB)

julia> @time a * (b * c); 0.000101 seconds (6 distributions: 1.906 KiB)

The results are consistent with the above. Although it makes an intuitive sense why the second is better (matrix-vector multiplication twice instead of large matrix-matrix multiplication).

I was wondering if Julia should optimize this, knowing what the sizes of the matrices are, and that could change the order of the operation in order to optimize it? Or am I just too lazy to wish for this or there are other technical problems that I do not see.

So this is what I get when I use dump () on (abc)

  head: Symbol call
  args: Array{Any}((4,))
    1: Symbol *
    2: Array{Float64}((100, 100)) [0.290788 -0.0601455 … -0.408164 1.16261; -0.539274 -1.56979 … 2.56233 0.806247; … ; 1.30981 -1.31929 … 1.38655 -1.89169; -1.58483 0.318804 … -0.0500151 2.13105]
    3: Array{Float64}((100, 100)) [-0.464882 1.60371 … -0.390234 0.605401; -1.06837 0.296049 … 0.759708 0.0124688; … ; -0.149613 -1.38653 … 0.284494 1.47524; 0.34351 0.420449 … 0.544973 1.85736]
    4: Array{Float64}((100, 1)) [1.64066; 0.593296; … ; 0.908361; 0.486164]
  typ: Any

dump (a * (b * s))

Expr
  head: Symbol call
  args: Array{Any}((3,))
    1: Symbol *
    2: Array{Float64}((100, 100)) [0.290788 -0.0601455 … -0.408164 1.16261; -0.539274 -1.56979 … 2.56233 0.806247; … ; 1.30981 -1.31929 … 1.38655 -1.89169; -1.58483 0.318804 … -0.0500151 2.13105]
    3: Expr
      head: Symbol call
      args: Array{Any}((3,))
        1: Symbol *
        2: Array{Float64}((100, 100)) [-0.464882 1.60371 … -0.390234 0.605401; -1.06837 0.296049 … 0.759708 0.0124688; … ; -0.149613 -1.38653 … 0.284494 1.47524; 0.34351 0.420449 … 0.544973 1.85736]
        3: Array{Float64}((100, 1)) [1.64066; 0.593296; … ; 0.908361; 0.486164]
      typ: Any
  typ: Any