rustc_codegen_gcc VS compiler-explorer

Alternatively, there's another initiative called codegen_gcc which is about using GCC as a backend for the rustc compiler. It's (much) more advanced in Rust support, but I am not sure how easy it would be to use a modified libgccjit from there.

In addition to what others have said about platform support, Rust is also on its way to gaining more platform support through rustc_codegen_gcc, the GCC codegen backend for rustc, as an alternative to the LLVM backend. That means many of the platforms GCC supports will suddenly become available with Rust.

Yeah, rustc_codegen_gcc is a GCC backend for rustc, and its making a lot of good regular progress.

gcc-rs is one of two projects for bringing Rust to gcc. gcc-rs is the more ambitious of the two, with an entirely new frontend. There is also rustc_codegen_gcc (https://github.com/rust-lang/rustc_codegen_gcc) that keeps the rustc frontend, and only swaps out LLVM for GCC at the codegen stage.

Fixing unwinding in release mode is still ungoing. I could use some help here, so anyone with some understanding of unwinding, landing pads or GCC, please come on this issue to discuss this.

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.

Good idea. I added the tag "help wanted" to the issue.

Also, there are indeed ABI issues, e.g. for 128-bit integers and NaN.

I'm excited about both the backend & the frontend.

There is also a project for rustc to use GCC instead of LLVM for codegen.

https://github.com/rust-lang/rustc_codegen_gcc

You said You won't get "extreme performance" from C++ because it is buried under the weight of decades of compatibility hacks.

Now your whole comment is about vector behavior. You haven't talked about what 'decades of compatibility hacks' are holding back performance. Whatever behavior you want from a vector is not a language limitation.

You could write your own vector and be done with it, although I'm still not sure what you mean, since once you reserve capacity a vector still doubles capacity when you overrun it. The reason this is never a performance obstacle is that if you're going to use more memory anyway, you reserve more up front. This is what any normal programmer does and they move on.

Show what you mean here:

https://godbolt.org/

I've never used ISPC. It's somewhat interesting although since it's Intel focused of course it's not actually portable.

I guess now the goal posts are shifting. First it was that "C++ as a language has performance limitations" now it's "rust has a vector that has a function I want and also I want SIMD stuff that doesn't exist. It does exist? not like that!"

Try to stay on track. You said there were "decades of compatibility hacks" holding back C++ performance then you went down a rabbit hole that has nothing to do with supporting that.

C++ Insights is available online at https://cppinsights.io/

It is also available at a touch of a button within the most excellent https://godbolt.org/

along side the button that takes your code sample to https://quick-bench.com/

Those sites and https://cppreference.com/ are what I'm using constantly while coding.

I recently discovered https://whitebox.systems/ It's a local app with a $69 one-time charge. And, it only really works with "C With Classes" style functions. But, it looks promising as another productivity boost.

[P&H RISC] https://www.google.com/books/edition/_/e8DvDwAAQBAJ

Compiler Explorer by Matt Godbolt [Godbolt] can help better understand what code a compiler generates under different circumstances.

[Godbolt] https://godbolt.org

The official CPU architecture manuals from CPU vendors are surprisingly readable and information-rich. I only read the fragments that I need or that I am interested in and move on. Here is the Intel’s one [Intel]. I use the Combined Volume Set, which is a huge PDF comprising all the ten volumes. It is easier to search in when it’s all in one file. I can open several copies on different pages to make navigation easier.

Intel also has a whole optimization reference manual [Intel] (scroll down, it’s all on the same page). The manual helps understand what exactly the CPU is doing.

[Intel] https://www.intel.com/content/www/us/en/developer/articles/t...

Personally, I believe in automated benchmarks that measure end-to-end what is actually important and notify you when a change impacts performance for the worse.

Let's compile it with https://godbolt.org/, turn on some optimisations and inspect the IR (-O2 -emit-llvm). Copying out the part that corresponds to the while loop:

  4:

resources were extra useful when building deeper intuitions about GPU performance for ML models at work and in graduate school.

- CMU's "Deep Learning Systems" Course is hosted online and has YouTube lectures online. While not generally relevant to software performance, it is especially useful for engineers interested in building strong fundamentals that will serve them well when taking ML models into production environments: https://dlsyscourse.org/

- Compiler Explorer is a tool that allows you easily input some code in and check how the assembly output maps to the source. I think this is exceptionally useful for beginner/intermediate programmers who are familiar with one compiled high-level language and have not been exposed to reading lots of assembly. It is also great for testing how different compiler flags affect assembly output. Many people used to coding in C and C++ probably know about this, but I still run into people who haven't so I share it whenever performance comes up: https://godbolt.org/

To really understand what's going on here we can look at the compiled assembly code. I'm working on a Mac and can do this using the objdump tool. Compiler Explorer is also a handy tool but doesn't seem to support Arm assembly which is what Rust will use when compiling on Apple Silicon.

Play around with it in godbolt if you're really curious: https://godbolt.org/

It sounds like you are very new to programming and C++. If you'll allow me to make a recommendation: trying to set up a C++ in VS Code is quite a difficult task for a beginner. There are a lot of trip ups -- the compiler you're using, how your Code Runner or tasks.json or launch.json are set up, whether you're using Makefiles or Cmake, etc. For beginning with C++, I would really recommend messing around with Compiler Explorer instead (https://godbolt.org/). It was originally designed to turn C++ code into assembly for debugging, but you can use it like a fast scratchpad for learning, and it auto rebuilds as you make changes so you can see errors quickly. Good luck!