ogv.js
PackageCompiler.jl
ogv.js | PackageCompiler.jl | |
---|---|---|
7 | 26 | |
1,182 | 1,373 | |
- | 0.7% | |
7.2 | 7.8 | |
3 days ago | 13 days ago | |
JavaScript | Julia | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ogv.js
-
"MP3 is dead" missed the real, much better story (2017)
Yeah, that's what they do using this https://github.com/brion/ogv.js/
- Making Python 100x faster with less than 100 lines of Rust
-
Google and Mozilla are working on iOS browsers that aren't based on WebKit
I've been told this at least three times now on HN over the years (pretty soon I'm going to start keeping a list of URLs so people know I'm not exaggerating.) Every single time it turns out that it isn't actually true.
It was added to desktop Safari. iOS Safari supports VP9 only in WebRTC. It may have changed, but I can't find any evidence that it has.
If you see it working somewhere, it is almost definitely using the polyfill[1].
[1]: https://github.com/brion/ogv.js/
-
How to stream OGG on iOS?
I found a library "ogv.js" that says it decodes .ogg/.webm using WebAssembly, and this demo plays on my iPhone SE3 in Safari.
-
Anti-innovative effects of Apple's prohibition of alternative browser engines
I believe Wikipedia has resorted to polyfilling it using this:
https://github.com/brion/ogv.js
That's great and all, but it has limitations, and obviously, is ludicrously less efficient than it should be.
-
Privacy analysis of FLoC
We already have JS/WebGL video decoders (e.g: Broadway.js, OGOV.js). Much of the earlier video playback/acceleration work was getting it accelerated on GPUs-- using DirectX, OpenGL, or other GPU programming standards.
-
WebCodecs is a flexible web API for encoding and decoding audio and video
This is great and overdue. Hopefully all major browsers will add some support for open source/royalty free codecs.
Emscripten/WebAssembly actually worked rather well with audio (OPUS is just awesome) but when it comes to video it's just unfeasible, especially if you are looking at doing low latency streaming. That said, I cannot fail to mention the incredible effort done by ogv.js [1] to make a/v decoding possible almost anywhere.
Looking forward to experiment with this new API.
[1] https://github.com/brion/ogv.js/
PackageCompiler.jl
-
Potential of the Julia programming language for high energy physics computing
Yes, julia can be called from other languages rather easily, Julia functions can be exposed and called with a C-like ABI [1], and then there's also various packages for languages like Python [2] or R [3] to call Julia code.
With PackageCompiler.jl [4] you can even make AOT compiled standalone binaries, though these are rather large. They've shrunk a fair amount in recent releases, but they're still a lot of low hanging fruit to make the compiled binaries smaller, and some manual work you can do like removing LLVM and filtering stdlibs when they're not needed.
Work is also happening on a more stable / mature system that acts like StaticCompiler.jl [5] except provided by the base language and people who are more experienced in the compiler (i.e. not a janky prototype)
[1] https://docs.julialang.org/en/v1/manual/embedding/
[2] https://pypi.org/project/juliacall/
[3] https://www.rdocumentation.org/packages/JuliaCall/
[4] https://github.com/JuliaLang/PackageCompiler.jl
[5] https://github.com/tshort/StaticCompiler.jl
- Strong arrows: a new approach to gradual typing
-
Making Python 100x faster with less than 100 lines of Rust
One of Julia's Achilles heels is standalone, ahead-of-time compilation. Technically this is already possible [1], [2], but there are quite a few limitations when doing this (e.g. "Hello world" is 150 MB [7]) and it's not an easy or natural process.
The immature AoT capabilities are a huge pain to deal with when writing large code packages or even when trying to make command line applications. Things have to be recompiled each time the Julia runtime is shut down. The current strategy in the community to get around this seems to be "keep the REPL alive as long as possible" [3][4][5][6], but this isn't a viable option for all use cases.
Until Julia has better AoT compilation support, it's going to be very difficult to develop large scale programs with it. Version 1.9 has better support for caching compiled code, but I really wish there were better options for AoT compiling small, static, standalone executables and libraries.
[1]: https://julialang.github.io/PackageCompiler.jl/dev/
-
What's Julia's biggest weakness?
Doesn’t work on Windows, but https://github.com/JuliaLang/PackageCompiler.jl does.
-
I learned 7 programming languages so you don't have to
Also, you can precompile a whole package and just ship the binary. We do this all of the time.
https://github.com/JuliaLang/PackageCompiler.jl
And getting things precompiled: https://sciml.ai/news/2022/09/21/compile_time/
-
Julia performance, startup.jl, and sysimages
You can have a look at PackageCompiler.jl
-
Why Julia 2.0 isn’t coming anytime soon (and why that is a good thing)
I think by PackageManager here you mean package compiler, and yes these improvements do not need a 2.0. v1.8 included a few things to in the near future allow for building binaries without big dependencies like LLVM, and finishing this work is indeed slated for the v1.x releases. Saying "we are not doing a 2.0" is precisely saying that this is more important than things which change the user-facing language semantics.
And TTFP does need to be addressed. It's a current shortcoming of the compiler that native and LLVM code is not cached during the precompilation stages. If such code is able to precompile into binaries, then startup time would be dramatically decreased because then a lot of package code would no longer have to JIT compile. Tim Holy and Valentin Churavy gave a nice talk at JuliaCon 2022 about the current progress of making this work: https://www.youtube.com/watch?v=GnsONc9DYg0 .
This is all tied up with startup time and are all in some sense the same issue. Currently, the only way to get LLVM code cached, and thus startup time essentially eliminated, is to build it into what's called the "system image". That system image is the binary that package compiler builds (https://github.com/JuliaLang/PackageCompiler.jl). Julia then ships with a default system image that includes the standard library in order to remove the major chunk of code that "most" libraries share, which is why all of Julia Base works without JIT lag. However, that means everyone wants to have their thing, be it sparse matrices to statistics, in the standard library so that it gets the JIT-lag free build by default. This means the system image is huge, which is why PackageCompiler, which is simply a system for building binaries by appending package code to the system image, builds big binaries. What needs to happen is for packages to be able to precompile in a way that then caches LLVM and native code. Then there's no major compile time advantage to being in the system image, which will allow things to be pulled out of the system image to have a leaner Julia Base build without major drawbacks, which would then help make the system compile. That will then make it so that an LLVM and BLAS build does not have to be in every binary (which is what takes up most of the space and RAM), which would then allow Julia to much more comfortably move beyond the niche of scientific computing.
- Is it possible to create a Python package with Julia and publish it on PyPi?
- GenieFramework – Web Development with Julia
-
Julia for health physics/radiation detection
You're probably dancing around the edges of what [PackageCompiler.jl](https://github.com/JuliaLang/PackageCompiler.jl) is capable of targeting. There are a few new capabilities coming online, namely [separating codegen from runtime](https://github.com/JuliaLang/julia/pull/41936) and [compiling small static binaries](https://github.com/tshort/StaticCompiler.jl), but you're likely to hit some snags on the bleeding edge.
What are some alternatives?
Broadway - A JavaScript H.264 decoder.
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
web-codecs - WebCodecs is a flexible web API for encoding and decoding audio and video.
julia - The Julia Programming Language
Mail-in-a-Box - Mail-in-a-Box helps individuals take back control of their email by defining a one-click, easy-to-deploy SMTP+everything else server: a mail server in a box.
Genie.jl - 🧞The highly productive Julia web framework
numexpr - Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
LuaJIT - Mirror of the LuaJIT git repository
jnumpy - Writing Python C extensions in Julia within 5 minutes.
Dash.jl - Dash for Julia - A Julia interface to the Dash ecosystem for creating analytic web applications in Julia. No JavaScript required.
poly-match - Source for the "Making Python 100x faster with less than 100 lines of Rust" blog post
Transformers.jl - Julia Implementation of Transformer models