I performed some benchmarks of simulating a complex AR(1) process. See this ipython notebook <http://nbviewer.ipython.org/gist/nbren12/d8fec9a9cdeb917258d0>. Julia is about 10x slower than the fortran code, and the fortran is only a few more lines of code. Python is my go-to language (no pun indented), and I could just use f2py to access this 10x speedup. Assuming I only care about julia's performance, and not about its other language features (ie. multiple dispatch, macros, etc), I could live with 2-5x slowdown compared to fortran. However, if I can expect these sorts of codes to run 10x slower than fortran, I think I would prefer "python +fortran+ f2py" over julia.
I have a few questions: 1) Am i doing something stupid 2) Are all Monte Carlo type codes susceptible to this slowdown? 3) Would the gap between julia and fortran narrow for higher dimensional processes? In general, I see the benefits of using a single language over many for a single project, and I am very excited about julia, but a 10x slowdown is a bit hard to stomach in these sorts of applications.
