Jason Merrill, Thank you for your speed up suggestions. Managed to get close to a factor of 2 speed up out of GaussLegendre. I quickly looked at GaussJacobi too and also got a significant speed up there... still more to do on that code. Alex
On Tuesday, 2 September 2014 20:52:28 UTC-4, Alex Townsend wrote: > > Both those tools look great. Trying them now. Thanks a bunch. > Alex > > On Tuesday, 2 September 2014 19:16:36 UTC-4, Jason Merrill wrote: >> >> On Tuesday, September 2, 2014 5:57:43 AM UTC-7, Alex Townsend wrote: >>> >>> >>> >>> On Tuesday, 2 September 2014 03:00:10 UTC-4, Jason Merrill wrote: >>>> >>>> On Monday, September 1, 2014 2:33:31 PM UTC-7, Alex Townsend wrote: >>>>> >>>>> I have written a package FastGauss.jl available here: >>>>> >>>>> https://github.com/ajt60gaibb/FastGauss.jl >>>>> >>>> >>>>> I am a Julia beginner (only been learning for 2 weeks) so I am >>>>> assuming the code can be >>>>> improved in a million and one ways. Please tell me if I've done >>>>> something that Julia does >>>>> not like. I am not sure if it is appropriate to make this an official >>>>> package. >>>>> >>>> >>>> One thing to look out for is making sure your functions have consistent >>>> return types. E.g. in >>>> https://github.com/ajt60gaibb/FastGauss.jl/blob/91e2ac656b856876563d5aacf7b5a405e068b3da/src/GaussLobatto.jl#L4 >>>> >>>> you have >>>> >>> Thanks! I tried to get the return types consistent, but obviously missed >>> a few. I've been trying to use @code_typed to tell me this >>> information, but reading the output is a little difficult (at the >>> moment). >>> >> >> I think the community as a whole would like to see better tooling around >> finding and fixing this kind of soft bug. >> >> You might check out https://github.com/tonyhffong/Lint.jl, and >> https://github.com/astrieanna/TypeCheck.jl. I haven't tried either of >> them myself yet, but I've heard people say good things about both of them. >> >> >
