On 24 September 2015 at 23:15, Marcio Sales <marciole...@hotmail.com> wrote:
> That is a meaningless comparison. First, you are not comparing loops, you >> are comparing matrix inversion. Second, neither Matlab nor Julia will >> natively perform a matrix inversion well. They are both going to use an >> external library (LAPACK) so what you are testing is the library, not the >> language. For example, Matlab almost certainly ships with Intel's MKL (math >> kernel libraries) which includes a call for matrix inversion that was >> carefully written by Intel employees to run as fast as possible on Intel >> CPUs. Julia cannot ship with MKL, but if you care enough it is probably >> possible to link to it. >> >> Daniel. >> > > Well, then did you just say that if one keeps using matlab in the way it > was meant to (matrices operations), there's no way Julia can beat it > currently (performancewise)? > > If the only thing you care about is performance with the linear algebra routines provided by LAPACK, there is no reason for you to stop using Matlab. Julia will not beat it. For reference, LAPACK provides routines for matrix inversion, matrix decomposition (QR, LU, SVD, etc) and linear least squares and eigenvalue problems. As a historical note, I will add that the whole reason why Matlab was invented was as a front-end for LINPACK (the ancestor of LAPACK). Cheers, DAniel.
