Hi all, (first post) I"m having my first look at julia and translated a pathtracer written in python into julia. (A pathtracer is a kind of raytracer)
The translation was relatively painless, and I've mimicked the python classes that I lost by using julia's compound types. Code is here => https://bitbucket.org/mikefc/julia-pathtracer/overview However, after going through performance tips and looking for low hanging fruit, the julia version is still 3x slower than the python version. Note: the python version does have core matrix/vector and intersection functions written in C, and I run it using pypy. What are some ways I can make the julia code faster? * Is there something in the way I'm systematically handling arrays/vectors which is leading to slowdown? * The algorithms/techniques are a direct translation of the python code. Is this style "not liked" by the compiler? * Are there better ways of passing around config information? (see Config.jl) The key difference between the python and julia code is that I've aggressively removed temporary vectors by doing nearly all calculations in pre-allocated memory. I started going down the same road with julia, and while I did see some improvements I didn't see enough improvement to implement it everywhere (it makes the code quite messy). I've toyed with parallel rendering (on multiple cores), but for the moment I'm just comparing single-core rendering speed. I've also had a look at the profiling information, and I didn't get a lot of it. Any help appreciated! thanks mike.
