Re:Comparison – R vs. Python: head to head data analysis
by ced on Wednesday October 14, 2015 @01:01PM
(#10387819)
it's still somewhat perplexing the extent to which vectorized code is necessarily slower
The vectorized code typically allocates all kinds of intermediate results (more GC, more memory accesses). Apparently, turning it into loops is less trivial than it seems.
I'm thinking that the future of GPU enabled languages will mean vectorized code will be faster, so I prefer languages with a bias towards vectorisation.
I share that concern. Julia has some libraries to support GPU programming, but I don't know of any plans to have the core compiler take advantage of it.
Re:Comparison – R vs. Python: head to head data analysis
by johnmyleswhite on Wednesday October 14, 2015 @01:14PM
(#10387911)
I think you may have misinterpreted that post. Look at the table under "Comparing Performance in R and Julia" again.
http://www.johnmyleswhite.com/notebook/2013/12/22/the-relati...
had worried me a couple of years ago. JMW shows that vectorized was much slower also in Julia (though still both faster than R - but that's not difficult).
Glad to see Julia is very fast in both cases, though it's still somewhat perplexing the extent to which vectorized code is necessarily slower. I'm thinking that the future of GPU enabled languages will mean vectorized code will be faster, so I prefer languages with a bias towards vectorisation.