

Fast Numeric Computation in Julia - Rickasaurus
http://julialang.org/blog/2013/09/fast-numeric/

======
StefanKarpinski
I should point out that many of these techniques are not specific to Julia,
although many of them are not so familiar to users of high-level languages
since one doesn't, for example, need to think about ordering of matrix
iterations when writing vectorized code. Those who write high-performance C
and Fortran array code will already be familiar with much of this advice.

~~~
ihnorton
It is remarkable to me that these kind of considerations _can even come up_ in
a language with the high-level expressiveness of Julia.

As I work with Julia (and read code in the base and packages), I am
continually impressed by the capability to work at so many different levels,
and the smoothness of the integration. From clean, readable, Python-like
"executable pseudocode"; to type annotations and generic code; to code-
generation with macros; to efficient data structures in-language --- and all
the way down into bit-fiddling, pointer arithmetic, and inspection of IR and
assembly.

As the blog post details, this layering allows a smooth transition from
"making it right" to "making it fast" within a single language, and I think we
are only seeing glimmers of the cohesiveness and network effects that this
enables.

------
StefanKarpinski
Discussion of the article on the julia-users mailing list:

[https://groups.google.com/forum/#!topic/julia-
users/d_ucezbI...](https://groups.google.com/forum/#!topic/julia-
users/d_ucezbI6X0)

