manylinux VS llvm-project

I use manylinux containers as the OS for compilation. It tries to ensure as much cross-os / libc / etc.. as much as possible for precompiled libraries. https://github.com/pypa/manylinux

Just to clarify for anyone who isn't aware, the "compiling issues", at least historically, have been that that Alpine uses musl, and PyPI's manylinux wheels are built against old glibc versions. So stuff like numpy that would trivially and quickly install from whl on glibc distros (like a bare-bones Ubuntu image) trigger compilations and the installation of build-only dependencies on Alpine.

That said, it looks like as of late-2021, at least some projects are offering musllinux wheels as well, per the discussion here: https://github.com/pypa/manylinux/issues/37 (not numpy, though: https://pypi.org/project/numpy/#files)

It's very hard. Incompatible glibc ABIs make this nigh impossible, there's a reason Steam installs a vcredistributable.dll for pretty much every game on Windows.

Look no further than the hoops you need jump through to distribute a Linux binary on PyPI [1]. Despite tons of engineering effort, and tons of hoop jumping from packagers, getting a non-trivial binary to run across all distros is still considered functionally impossible.

[1]: https://github.com/pypa/manylinux

As a user, if you build every python package from source, it's ok. But if you a maintainer of an OSS project and you need to publish binary packages for it, then you will hit the trouble. Binaries built on Ubuntu 20.04 can only support Ubuntu 20.04 and newer. So you'd better to choose an older Linux release to target broader users. Now most python packages choose CentOS 6 or 7. See https://github.com/pypa/manylinux/issues/1012 for more details. They need help!

I recently learned that Clang supports this kind of cross-compiling out of the box. https://mcilloni.ovh/2021/02/09/cxx-cross-clang/

The main difference is that Clang does not ship with headers/libraries for different platforms, as Zig appears to do. You need to give Clang a "sysroot" -- a path that has the headers/libraries for the platform you want to compile for.

If you create a bunch of sysroots for various architectures, you can do some pretty "easy" cross-compiling with just a single compiler binary. Docker can be a nice way of packaging up these sysroots (especially combined with Docker images like manylinux: https://github.com/pypa/manylinux). Gone are the days when you had to build a separate GCC cross-compiler for each platform you want to target.

Now you come and use manylinux to build. (https://github.com/pypa/manylinux) so you are based on the CentOS 7 toolchain (at best if you use manylinux2014) or Debian 9 toolchain (if you use manylinux_2_24).

I think the generally accepted way to do that would be a container image running a relatively old distribution. This is exactly what python packages do when they need to distribute binary packages on linux [0]. You are supposed to compile the package in a container (or VM) that runs CentOS 7 (or older if you want broader support), although now the baseline is moving gradually to Debian 9.

[0]: https://github.com/pypa/manylinux

'Computer Architeture: A Quantitative Apporach" and/or more specific design types (mips, arm, etc) can be found under the Morgan Kaufmann Series in Computer Architeture and Design.

"Getting Started with LLVM Core Libraries: Get to Grips With Llvm Essentials and Use the Core Libraries to Build Advanced Tools "

"The Architecture of Open Source Applications (Volume 1) : LLVM" https://aosabook.org/en/v1/llvm.html

"Tourist Guide to LLVM source code" : https://blog.regehr.org/archives/1453

llvm home page : https://llvm.org/

llvm tutorial : https://llvm.org/docs/tutorial/

llvm reference : https://llvm.org/docs/LangRef.html

learn by examples : C source code to 'llvm' bitcode : https://stackoverflow.com/questions/9148890/how-to-make-clan...

See

https://github.com/llvm/llvm-project/issues/88344

https://fortran-lang.discourse.group/t/flang-new-how-to-forc...

You can never mistake type_declaration with an identifier, otherwise the program will not work. Aside from that constraint, you are free to name them whatever you like, there is no one standard, and each parser has it own naming conventions, unless you are planning to use something like LLVM. If you are interested, you can see examples of naming in different language parsers in the AST Explorer.

> There is one way to make the LLVM JIT compiler more usable, but I fear it’s going to take years to be implemented: being able to cache and reuse compiled queries.

Actually, it's implemented in LLVM for years :) https://github.com/llvm/llvm-project/commit/a98546ebcd2a692e...

> It's true, this was a CVE in Rust and not a CVE in C++, but only because C++ doesn't regard the issue as a problem at all. The problem definitely exists in C++, but it's not acknowledged as a problem, let alone fixed.

Can you find a link that substantiates your claim? You're throwing out some heavy accusations here that don't seem to match reality at all.

Case in point, this was fixed in both major C++ libraries:

https://github.com/gcc-mirror/gcc/commit/ebf6175464768983a2d...

https://github.com/llvm/llvm-project/commit/4f67a909902d8ab9...

So what C++ community refused to regard this as an issue and refused to fix it? Where is your supporting evidence for your claims?

For everyone else looking for the magic in this almost 7k lines monster, look at line 6610 [1].

[1] https://github.com/llvm/llvm-project/blob/8ec28af8eaff5acd0d...

Through value tracking. It's actually LLVM that does this, GCC probably does it as well, so in theory explicit bounds checks in regular C code would also be removed by the compiler.

How it works exactly I don't know, and apparently it's so complex that it requires over 9000 lines of C++ to express:

https://github.com/llvm/llvm-project/blob/main/llvm/lib/Anal...

https://github.com/llvm/llvm-project/blob/main/flang/docs/F2...

• Go • Rust • Lua • pure C (sans C++) • 6502 assembly • WebAssembly • compiler backends, like LLVM or Cranelift