DNF2

9 ms·

1.
by DNF2 10mo ago
First of all, I think this sort of aggressive tone is unwarranted. Secondly, I think it's on you to clarify that you were talking specifically and exclusively about static compilation to standalone binaries. Re-reading your first post
2.
by DNF2 10mo ago
I'm not exactly sure what you don't believe, your comment is hard to follow, or relies on premises I haven't detected. What you are describing in your first paragraph is somewhat reminiscent of dynamic dispatch, which Julia d
3.
by DNF2 10mo ago
This is not how I understand the performance model. Allowing invokation of the compiler at runtime is definitely not something that is done for performance, but for dynamism, to allow some code to run that could not otherwise be run. In p
4.
by DNF2 11mo ago
> Julia is fastest with immutable structures--why provide a built-in syntax for complex assignment to mutable types, but then relegate lenses to a library that only FP aficionados will use? This is not really accurate. Performance in Jul
5.
by DNF2 11mo ago
Actually, very nearly so: https://typst.app/universe/package/soviet-matrix/
6.
by DNF2 11mo ago
Interesting. I have not experienced that, except when trying out the pre-release version of tinymist, and did some messy multiple view+cropping into a big pdf (testing out the new pdf-image stuff.) I chalked it up to it being new and beta.
7.
by DNF2 11mo ago
> 2. (minor compared to Overleaf) typst compiles faster. I would argue that this isn't minor. At least in my opinion, it makes a big difference. Overleaf, already 3 pages into a document, with a couple of TikZ figures, was getting s
8.
by DNF2 11mo ago
As long as Typst is on version 0.x,you should probably expect breaking changes. There is talk about changing even part of the parsing rules. This is the risk of being an early adopter. Once v1.0 is out, I hope it will stabilize for the long
9.
by DNF2 1y ago
But those are not languages, but frameworks, and are not general enough to solve many problems, especially outside of machine learning.
10.
by DNF2 2y ago
That is not really correct. Type instabilities tend to disappear at function boundaries, which is one of the reasons why using functions is so heavily promoted in Julia, it helps keep type instabilites 'localized'.
11.
by DNF2 2y ago
Then you are back to the "two language problem". I'm sure that's not a problem for you and for many others, but there is a reason it has its own, widely known name. It really is a problem for people who are mostly not so
12.
by DNF2 2y ago
"Clanky"? That is a word I would use when comparing Julia and Python, but I would reverse the roles. I mean, python works well, and has almost everything, but it really feels, well, clanky.
13.
by DNF2 2y ago
No, they are not using the same algorithm: https://laurmaedje.github.io/posts/layout-models/
14.
by DNF2 2y ago
That article was about handling of "Missing" values (which Julia now had natively), and a wish for inclusion of an 80-bit float type. I don't know what languages has that, but you can have 128bit, 256bit and even larger float
15.
by DNF2 2y ago
Could you elaborate on the numerical precision issue regarding Julia?
16.
by DNF2 2y ago
I didn't even mention the dot operator syntax (.*,.^,./) used in Matlab, while numpy uses only implicit broadcasting. On the other hand, numpy can partially leverage map, filter, comprehension (though with performance loss). Julia
17.
by DNF2 2y ago
I forgot to mention the difference in function passing, the fact that Matlab passes arguments by value (unless it's a `handle` class) makes it really hard to do in-place transformations, as in passing an array to a function and modifyi
18.
by DNF2 2y ago
In some cases, applying a limited set of basic operations might make up a significant part of development time, but in my experience most of the time is spent designing algorithms, parsing function input and managing the flow of vectorized
19.
by DNF2 2y ago
Yes, python exposes a limited list of names that map to operators, like __add__, __sub__, __ne__, __or__, etc. The list is large enough that it covers most normal usage, but the semantic meaning of the operators is normally fixed, so creati
20.
by DNF2 2y ago
Both zero-based and one-based indexing is common in mathematics, for example polynomials, exponential series, transforms, etc. are often zero-based. But in most of the literature that I've seen, vectors and matrices tend to number elem
21.
by DNF2 2y ago
I must agree with the other poster that there are key differences between numpy and Matlab (and Julia). All 1D/2D arrays in both Matlab and Julia come endowed with linear algebra semantics, so that `A*B` is a matrix product, while in n
22.
by DNF2 2y ago
You are mostly correct, though I want to point out that N-dim arrays are different from matrices. In Matlab everything is a matrix, unless it is a higher-dimensional array. This means that any 'scalar value' is actually a 1x1 matr
23.
by DNF2 3y ago
Well, it's called JuPyteR (my capitalisation), and originally supported Julia, Python and R. The exact provenance of the name is a bit unclear, but it's either deliberate or a happy coincidence. Pluto.jl is also 'like Jupyter
24.
by DNF2 3y ago
Loopvectorization exploits avx512, when available. How is that achieved?
25.
by DNF2 3y ago
First of all, Mojo is quite new. Secondly, there might not be much CPU performance left on the table for that benchmark, no matter how much money you throw at it.
26.
by DNF2 3y ago
You must mean REPL, not notebook. I've been following the community since before the move to Discourse, and "use the REPL" surely outnumbers "use a notebook" by orders of magnitude.
27.
by DNF2 3y ago
I can confirm that there were multiple (heated) arguments on Discourse, where some posters completely dismissed the need for debuggers in general. I remember it quite well. It was very strange, but I don't think it says anything about
28.
by DNF2 3y ago
It's really all down to your tone and attitude. If you're hostile, demanding and negative, you will indeed get pushback, but that's human nature. Some people feel that they should get to act like a prick, while everyone else
29.
by DNF2 3y ago
You make it sound a bit like they optimized the heck out of Julia, while the Mojo sample was a naive little thing in a new innocent language. The reality is that the Julia optimization was just a rewrite to use the same algorithm as Mojo, a
30.
by DNF2 3y ago
I don't really believe you ran either the Mojo or the Julia code. There's no way your single-threaded C code outperformed multi-threaded simd optimized Julia or Mojo. It's flat out impossible. The only other explanation is if

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