To give you some context,
I am currently implementing a simple finite element solver in Julia. I am getting run-times that are 70% of a Matlab code. (Both codes are essential equivalent in structure.) I've run some profiles on my Julia code and I find that most of the run-time is taken up by the linear system solver (essentially the "\" operator in $K \backslash F$ where $K$ is a sparse symmetric positive definite matrix and $F$ is a vector.)
I've tried looking up efficient solvers in Julia. I've come across the MUMPS package but I haven't used it yet. (I'm planning on giving it a go soon and will update this question when I do.)
More interestingly I came across this thread on the julia-users google-group which has a lot of content on how Matlab implements its (very efficient) solver.
My question is, what is the most efficient way of implementing a linear solver in Julia? Does the backslash operator choose the most efficient solution algorithm?