Hi

1) Yes, we pre-compiled the function.

2) As I mentioned before, we tried the code with and without type 
declaration, it makes a difference.

3) The variable names turns out to be quite useful because this code will 
be eventually nested into a much larger project where it is convenient to 
have very explicit names.

Thanks 

On Monday, June 16, 2014 12:13:44 PM UTC-4, Dahua Lin wrote:
>
> First, I agree with John that you don't have to declare the types in 
> general, like in a compiled language. It seems that Julia would be able to 
> infer the types of most variables in your codes.
>
> There are several ways that your code's efficiency may be improved:
>
> (1) You can use @inbounds to waive bound checking in several places, such 
> as line 94 and 95 (in RBC_Julia.jl)
> (2) Line 114 and 116 involves reallocating new arrays, which is probably 
> unnecessary. Also note that Base.maxabs can compute the maximum of absolute 
> value more efficiently than maximum(abs( ... ))
>
> In terms of measurement, did you pre-compile the function before measuring 
> the runtime?
>
> A side note about code style. It seems that it uses a lot of Java-ish 
> descriptive names with camel case. Julia practice tends to encourage more 
> concise naming.
>
> Dahua
>
>
>
> On Monday, June 16, 2014 10:55:50 AM UTC-5, John Myles White wrote:
>>
>> Maybe it would be good to verify the claim made at 
>> https://github.com/jesusfv/Comparison-Programming-Languages-Economics/blob/master/RBC_Julia.jl#L9
>>  
>>
>> I would think that specifying all those types wouldn’t matter much if the 
>> code doesn’t have type-stability problems. 
>>
>>  — John 
>>
>> On Jun 16, 2014, at 8:52 AM, Florian Oswald <florian...@gmail.com> 
>> wrote: 
>>
>> > Dear all, 
>> > 
>> > I thought you might find this paper interesting: 
>> http://economics.sas.upenn.edu/~jesusfv/comparison_languages.pdf 
>> > 
>> > It takes a standard model from macro economics and computes it's 
>> solution with an identical algorithm in several languages. Julia is roughly 
>> 2.6 times slower than the best C++ executable. I was bit puzzled by the 
>> result, since in the benchmarks on http://julialang.org/, the slowest 
>> test is 1.66 times C. I realize that those benchmarks can't cover all 
>> possible situations. That said, I couldn't really find anything unusual in 
>> the Julia code, did some profiling and removed type inference, but still 
>> that's as fast as I got it. That's not to say that I'm disappointed, I 
>> still think this is great. Did I miss something obvious here or is there 
>> something specific to this algorithm? 
>> > 
>> > The codes are on github at 
>> > 
>> > https://github.com/jesusfv/Comparison-Programming-Languages-Economics 
>> > 
>> > 
>>
>>

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