On Thursday, May 12, 2016 at 8:51:44 AM UTC-4, Miguel Bazdresch wrote: > > honestly I've been testing out different devectorizations of my algorithms >> and I keep getting slower results, not faster, so either I really suck at >> writing for loops or Julia is doing a good job with my vectorized code. >> > Make sure your loops are in a function — don't benchmark in global scope (see the performance tips sections of the manual). Try running your function through @code_warntype myfunction(args...) and see if it warns marks any variables as type "ANY" (which indicates a type instability in your code, see the performance tips),
Also, if you do "@time myfunc(args...)" and it indicates that you did a huge number of allocations, you could either have a type instability or be allocating new arrays in your inner loops (it is always better to allocate arrays once outside your inner loops and then update them in-place as needed).
