On Friday, May 1, 2015 at 3:25:50 AM UTC-5, 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). > > 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/ > . >
All benchmarks are flawed in that sense--a single benchmark can't tell you everything. The Julia performance benchmarks are testing algorithms expressed in the langauges themselves. It is not a test of foreign-function interfaces and BLAS implementations, so the benchmarks don't test that. This has been discussed at length--as one example, see https://github.com/JuliaLang/julia/issues/2412.
