V8 VS julia

https://chromium.googlesource.com/v8/v8.git/+/HEAD/include/c...

Due to the nature of web engine workloads migrating objects to being GC'd isn't performance negative (as most people would expect). With care it can often end up performance positive.

There are a few tricks that Oilpan can apply. Concurrent tracing helps a lot (e.g. instead of incrementing/decrementing refs, you can trace on a different thread), in addition when destructing objects, the destructors typically become trivial meaning the object can just be dropped from memory. Both these free up main thread time. (The tradeoff with concurrent tracing is that you need atomic barriers when assigning pointers which needs care).

This is on top of the safey improvements you gain from being GC'd vs. smart pointers, etc.

One major tradeoff that UAF bugs become more difficult to fix, as you are just accessing objects which "should" be dead.

> If that standard library would be written in JS, a new browser (or rather a new JS engine being a part of the browser) could just use some existing implementation

That sounds great, but I'm doubtful of the simplicity behind this approach.

If my understanding is correct, v8 has transitioned to C++[0] and Torque[1] code to implement the standard library, as opposed to running hard-coded JavaScript on setting up a new context.

I suspect this decision was made as a performance optimization, as there would obviously be a non-zero cost to parsing arbitrary JavaScript. Therefore, I doubt a JavaScript-based standard library would be an acceptable solution here.

[0]: https://github.com/v8/v8/tree/main/src/runtime

C++ lets you write anything you can imagine, and the language features and standard library often facilitate that. The committee espouses the view that they want to provide many "zero [runtime] cost," abstractions. Anybody can contribute to the language, although the committee process is often slow and can be political, each release the surface area and capability of the language gets larger.

I believe Hazard Pointers are slated for C++26, and these will add a form "free later, but not quite garbage collection" to the language. There was a talk this year about using hazard pointers to implement a much faster std::shared_ptr.

It's a language with incredible depth because so many different paradigms have been implemented in it, but also has many pitfalls for new and old users because there are many different ways of solving the same problem.

I feel that in C++, more than any other language, you need to know the actual implementation under the hood to use it effectively. This means knowing not just what the language specifies, but can occaissionally require knowing what GCC or Clang generate on your particular hardware.

Many garbage collected languages are written in or have parts of their implementations in C++. See JS (https://github.com/v8/v8)and Java GC (https://github.com/openjdk/jdk/tree/36de19d4622e38b6c00644b0...)

I am not an expert on Java (or C++), so if someone knows better or can add more please correct me.

Remember that we earlier established that every source gets parsed into an AST at some point before it gets compiled or interpreted. For example, platforms like Nodejs and chromium-based browsers use Gooogle's V8 engine behind the scenes to run JavaScript and of course, some AST parsing is always involved before the interpreter kicks in. I looked V8's source and I discovered it uses its own internal parser to achieve this.

In the source code of the Node.js opensource project, lib folder contains JavaScript code, mostly wrappers over C++ and function definitions. On the contrary, src folder contains C++ implementations of the functions, which pulls dependencies from the V8 project, the libuv project, the zlib project, the llhttp project, and many more - which are all placed at the deps folder.

Here is the implementation of of Array. prototype.map in V8. It's written in a language called Torque which appears to be a special language just for the v8 engine.

It sounds like you want to know how JavaScript is implemented in the browser. The thing is, there is no universal implementation for JavaScript. JavaScript defines a specification that must be adhered to, and then each browser vendor can implement it in whatever way they see fit, as long as it does the specified things. For example (and I'm not saying this is the case) it's entirely possible for Chrome to implement Array.sort() using merge sort, while Firefox implements it as quick sort. You can try to find the source code for the implementation in a certain browser, but that will not be universal. I imagine you can find out how it works in Chrome somewhere in https://chromium.googlesource.com/v8/v8.git, though I'm not sure exactly where.

34. Julia - $74,963

I don't believe there is any official documentation on this, but https://github.com/JuliaLang/julia/pull/49430 for example added prefetching to the marking phase of a GC which saw speedups on x86, but not on M1.

3. dispatch on all the arguments

the first solution is clean, but people really like dispatch.

the second makes calling functions in the function call syntax weird, because the first argument is privileged semantically but not syntactically.

the third makes calling functions in the method call syntax weird because the first argument is privileged syntactically but not semantically.

the closest things to this i can think of off the top of my head in remotely popular programming languages are: nim, lisp dialects, and julia.

nim navigates the dispatch conundrum by providing different ways to define free functions for different dispatch-ness. the tutorial gives a good overview: https://nim-lang.org/docs/tut2.html

lisps of course lack UFCS.

see here for a discussion on the lack of UFCS in julia: https://github.com/JuliaLang/julia/issues/31779

so to sum up the answer to the original question: because it's only obvious how to make it nice and tidy like you're wanting if you sacrifice function dispatch, which is ubiquitous for good reason!

https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md

Visit official site: https://julialang.org/

No. It runs natively on ARM.

julia> versioninfo() Julia Version 1.9.3 Commit bed2cd540a1 (2023-08-24 14:43 UTC) Build Info: Official https://julialang.org/ release

https://github.com/JuliaLang/julia/issues/51086#issuecomment...

So while this "fixes" the issue, it'll introduce a confusing time delay between you freeing the memory and you observing that in `htop`.

But according to https://jemalloc.net/jemalloc.3.html you can set `opt.muzzy_decay_ms = 0` to remove the delay.

Still, the musl author has some reservations against making `jemalloc` the default:

https://www.openwall.com/lists/musl/2018/04/23/2

> It's got serious bloat problems, problems with undermining ASLR, and is optimized pretty much only for being as fast as possible without caring how much memory you use.

With the above-mentioned tunables, this should be mitigated to some extent, but the general "theme" (focusing on e.g. performance vs memory usage) will likely still mean "it's a tradeoff" or "it's no tradeoff, but only if you set tunables to what you need".

I have asked about Julia's reproducibility story on the Guix mailing list in the past, and at the time Simon Tournier didn't think it was promising. I seem to recall Julia itself didnt have a reproducible build. All I know now is that github issue is still not closed.

https://github.com/JuliaLang/julia/issues/34753

I don't really know what kind of rebuttal you're looking for, but I will link my HN comments from when this was first posted for some thoughts: https://news.ycombinator.com/item?id=31396861#31398796. As I said, in the linked post, I'm quite skeptical of the business of trying to assess relative buginess of programming in different systems, because that has strong dependencies on what you consider core vs packages and what exactly you're trying to do.

However, bugs in general suck and we've been thinking a fair bit about what additional tooling the language could provide to help people avoid the classes of bugs that Yuri encountered in the post.

The biggest class of problems in the blog post, is that it's pretty clear that `@inbounds` (and I will extend this to `@assume_effects`, even though that wasn't around when Yuri wrote his post) is problematic, because it's too hard to write. My proposal for what to do instead is at https://github.com/JuliaLang/julia/pull/50641.

Another common theme is that while Julia is great at composition, it's not clear what's expected to work and what isn't, because the interfaces are informal and not checked. This is a hard design problem, because it's quite close to the reasons why Julia works well. My current thoughts on that are here: https://github.com/Keno/InterfaceSpecs.jl but there's other proposals also.

Doesn't musl have the same issue? https://github.com/JuliaLang/julia/issues/34726#issuecomment...

I also wonder about OSX's libc. Newer versions seem to have some sort of locking https://github.com/apple-open-source-mirror/Libc/blob/master...

but older versions (from 10.9) don't have any lockign: https://github.com/apple-oss-distributions/Libc/blob/Libc-99...