I have been spending the past weeks trying to really understand how to
implement efficient code.
As far as I can tell (from first hand experience), Julia really does
give you a prominent edge over R and Matlab in terms of performance.
However, I also think that there are currently a lot of ways to shoot
yourself in the foot (accidental type instability and memory allocation
are the most prominent of those in my experience).
So currently I don't think that Julia allows you to naively write
"simple and efficient code", iff you are not used to the language. In my
opinion, you really do need to get to know the language before simple
code becomes efficient as well.
Given that we are not at version 1.0 yet, I don't mind that at all. I
see it like this: If you know what to look out for, the code is usually
pretty competitive with C (about a factor of 2 to 3 currently for my
code). I rather have the developers focus on improving the potential
performance, than on making it "idiot proof" just yet. I think the later
is best tackled after the more pressing issues are taken care of.
That being said, I do think one should be careful of how Julia is
advertised by word of mouth. The comparison to Matlab, which has a very
similar syntax but (I think) a very different way of efficient coding,
can be a red herring and give rise to false expectations. I don't think
you can currently just copy and paste Matlab code and expect it to be
faster.
On 2015-09-24 14:17, Marcio Sales wrote:
Wow. All this discussion to make Julia only /as fast as/ the old
scripting languages? I gotta say that worried me a bit. What do you do
when there's no code to compare? How will you know that it was really
a good idea switching from Matlab/Python to Julia?
Considering what the develops proudly advertize about performance
(what I think is why most people would even consider changing to it),
shouldn't the language be designed as to put the user in the best
performant direction most of the time? Matlab does a good job on that
with fewer but simplified and efficient data structures, supporting
vectorized code etc. In my short experience with Julia, it seems that
there are a lot of ways to do the same thing, some of which very bad
in terms of performance, like the original code in this post. If Julia
can't be easily faster and less verbose than R for example, we could
just forget about it...
