rustc_codegen_cranelift
julia
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rustc_codegen_cranelift | julia | |
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44 | 350 | |
1,438 | 44,469 | |
5.5% | 0.8% | |
9.7 | 10.0 | |
2 days ago | 6 days ago | |
Rust | Julia | |
Apache License 2.0 | MIT License |
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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.
rustc_codegen_cranelift
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Cranelift code generation comes to Rust
Windows is supported. See https://github.com/rust-lang/rustc_codegen_cranelift/issues/....
- What part of Rust compilation is the bottleneck?
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A Guide to Undefined Behavior in C and C++
> When this happens, it seems like it'll be possible to get the LLVM bits out of the bootstrap process and lead to a fully self-hosted Rust.
What do you mean by "when this happens"? GP's point is that this has already happened: the Cranelift backend is feature-complete from the perspective of the language [0], except for inline assembly and unwinding on panic. It was merged into the upstream compiler in 2020 [1], and a compiler built with only the Cranelift backend is perfectly capable of building another compiler. LLVM hasn't been a necessary component of the Rust compiler for quite some time.
[0] https://github.com/bjorn3/rustc_codegen_cranelift
[1] https://github.com/rust-lang/rust/pull/77975
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What are some stuff that Rust isn't good at?
Note that the Cranelift codegen will eventually become standard for debug builds to speed them up.
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Rust port of B3 from WebKit, LLVM-like backend
Maybe one day we'll have rustc b3 backend like what they did with Cranelift
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Any alternate Rust compilers?
Additionally, there is gcc codegen for rustc (https://github.com/rust-lang/rustc_codegen_gcc), which is not a compiler per se, but an alternative code generator, with more architectures supported and other nice things. It's also coming along, but there's still a lot of work to do there too. There's also Cranelift codegen (https://github.com/bjorn3/rustc_codegen_cranelift), which is designed to make debug builds faster, but this is not as exciting/useful as the other 2.
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Capsules, reactive state, and HSR: Perseus v0.4.0 goes stable!
For the instant reloading, that's in Sycamore, so you should speak to its devs, but as for the alternative compiler backend, it's not my project, but it uses Cranelift and works pretty well! See https://github.com/bjorn3/rustc_codegen_cranelift for details.
- Security Engineer looking for ways to see if any of my tasks could slowly be ported to Rust or should I just stick with Python.
- Rust is now officially supported on some Infineon microcontrollers! (more to come later this year)
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Improving Rust compile times to enable adoption of memory safety
The more immediate goal of "distribute the cranelift backend as a rustup component" has been making good progress and seems like it might happen relatively soon https://github.com/bjorn3/rustc_codegen_cranelift/milestone/...
julia
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Top Paying Programming Technologies 2024
34. Julia - $74,963
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Optimize sgemm on RISC-V platform
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.
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Dart 3.3
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!
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Julia 1.10 Highlights
https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md
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Best Programming languages for Data Analysis📊
Visit official site: https://julialang.org/
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Potential of the Julia programming language for high energy physics computing
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
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Rust std:fs slower than Python
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".
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Eleven strategies for making reproducible research the norm
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
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Julia as a unifying end-to-end workflow language on the Frontier exascale system
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.
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Getaddrinfo() on glibc calls getenv(), oh boy
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...
What are some alternatives?
wasmtime - A fast and secure runtime for WebAssembly
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
gccrs - GCC Front-End for Rust
NetworkX - Network Analysis in Python
sccache - Sccache is a ccache-like tool. It is used as a compiler wrapper and avoids compilation when possible. Sccache has the capability to utilize caching in remote storage environments, including various cloud storage options, or alternatively, in local storage.
Lua - Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description.
mrustc - Alternative rust compiler (re-implementation)
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
cranelift-jit-demo - JIT compiler and runtime for a toy language, using Cranelift
Numba - NumPy aware dynamic Python compiler using LLVM
tch-rs - Rust bindings for the C++ api of PyTorch.
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp