On Friday, May 1, 2015 at 4:25:50 AM UTC-4, Steven Sagaert wrote: > > I think the performance comparisons between Julia & Python are flawed. > They seem to be between standard Python & Julia but since Julia is all > about scientific programming it really should be between SciPi & Julia. > Since SciPi uses much of the same underlying libs in Fortran/C the > performance gap will be much smaller and to be really fair it should be > between numba compiled SciPi code & julia. I suspect the performance will > be very close then (and close to C performance). >
Why should Julia be limited to scientific programming? I think it can be a great language for general programming, for the most part, I think it already is (it can use some changes for string handling [I'd like to work on that ;-)], decimal floating point support [that is currently being addressed, kudos to Steven G. Johnson], maybe some better language constructs to allow better software engineering practices [that is being hotly debated!], and definitely a real debugger [I think keno is working on that]). Comparing Julia to Python for general computing is totally valid and interesting. Comparing Julia to SciPy for scientific computing is also totally valid and interesting. Similarly the standard benchmark (on the opening page of julia website) > between R & julia is also flawed because it takes the best case scenario > for julia (loops & mutable datastructures) & the worst case scenario for R. > When the same R program is rewritten in vectorised style it beat julia see > https://matloff.wordpress.com/2014/05/21/r-beats-python-r-beats-julia-anyone-else-wanna-challenge-r/ > . > > So my interest in julia isn't because it is the fastest scientific high > level language (because clearly at this stage you can't really claim that) > but because it's a clean interesting language (still needs work for some > rough edges of course) with clean(er) & clear(er) libraries and that gives > reasonable performance out of the box without much tweaking. >
