JuliaLang/julia — comment on commit 1abf6194aabd5afd5b0c923707deb59537ac5ecc
File:  line 0
By StefanKarpinski:

V8 is very impressive. I'm running an oldish version that happens to be the V8 that the version of Node.js that my MacPorts setup installs is linked against. It's not ancient, but it's not new either. I should really hand-install the latest version of Node and re-run all the benchmarks. Another way to look at the NumPy/V8 comparison is that NumPy is kinda slow given that all it's doing is calling out to C. I *so* want to get close to C on all of these benchmarks. I know you do too. Then we're untouchable on performance. If we can do automatic polyhedral loop transformations and auto-parallelization too, then we'll start beating C, which will be completely insane.

I would also really like to figure out how to actually do the sorts of optimizations that we originally envisioned array comprehensions giving us and that we have though about symbolic optimizations providing too. I bet that actually having to do those transposes before calling the matrix multiplies is a huge part of why C is beating us on the randmatstat benchmark. Matlab is probably actually calling DGEMM with the transpose option on and that it's the other higher-level object manipulations that is slowing it down.