`crandn() = complex128(randn(),randn())/sqrt(2.)` should get you even closer to fortran.
-Mike On Sat, Sep 13, 2014 at 5:01 PM, Leah Hanson <[email protected]> wrote: > Lint.jl is also good for checking that, depending on how much time you want > to spend learning to read the output of code_typed. > > On Sat, Sep 13, 2014 at 3:27 PM, Elliot Saba <[email protected]> wrote: >> >> A good way to track down performance issues like this is to use >> @code_typed to output the typed code in your function and look for places >> where type inference doesn't know what to do; e.g. large type unions, Any >> types, etc.... This is often caused by a variable taking on multiple >> separate types over its lifetime within the function and can cause slowdowns >> inside inner loops. >> -E >> >> On Sat, Sep 13, 2014 at 1:13 PM, Noah Brenowitz <[email protected]> wrote: >>> >>> now i am pretty impressed. >>> >>> On Saturday, September 13, 2014 4:12:07 PM UTC-4, Noah Brenowitz wrote: >>>> >>>> I just replaced u = u0, with u = complex128(u0) in the julia code. Now >>>> it is only 2x as slow as fortran. >> >> >
