Hi Joseph,

Have you read 
http://julia.readthedocs.org/en/release-0.3/manual/performance-tips/ ?

I didn't read your code in detail, but a superficial read suggests that your 
code has a lot of type-instability, which is a showstopper for Julia.

 -- John

On Nov 30, 2014, at 4:58 PM, Joseph Ellsworth <[email protected]> wrote:

> Just finished some basic tests comparing the lua jit and Julia for the kinds 
> of statistical functions we commonly compute.   It essentially loads  70K  1 
> minute bar records and computes a sma(14) and sma(600) for every row in the 
> file.  This time I included source code so  others can figure out what I 
> missed.   It is admittedly a simplified case but I have found that if this 
> function runs fast the rest of our system tends to run fast so I consider it 
> a realistic starting benchmark. 
> 
> http://bayesanalytic.com/lua_jit_faster_than_julia_stock_prediction/   
> 
> The results were not what I expected.     I expected Julia to blow away lua 
> even with a jit due to the fact that I could allocate memory for result 
> arrays in typed arrays in Julia as blocks and couldn't figure out how to do 
> the same in lua.  In addition the lua array index access seem more like a 
> hash rather than a pure numeric array index which should give Julia a 
> substantial advantage when looping across items in an array.    What I found 
> is that Lua jit out performed Julia in all but 1 test even if you don't 
> consider Julia's horrible start-up performance.      
> 
> I am hoping that somebody finds a mistake that would make Julia out perform 
> as I really want to love it.    I like the Julia community  I also really 
> like the multi-dispatch function system.   The Julia community seems to be 
> working at a incredible velocity but Julia's poor error messages,  slow 
> startup time and letting lua beat them makes me skeptical for investing in it 
> for larger projects.    On the other-hand Lua has been around for a long time 
> and is used as a scripting engine in many games and consoles  and is unlikely 
> to go away anytime soon. 
> 
> If any of you produce a better Julia version that performs better then let me 
> know and I will add it to the original article.    If any of you have a 
> chance to port the same code to Python to using pypy,  Java, Scala, C  then 
> let me know and I will add it to the original article. 

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