arewefastyet VS compiler-explorer

That page averages all the builds across different code bases. It doesn’t specify which version/tag of which code base, nor does it talk about the hardware.

https://arewefastyet.pages.dev/ - This page tracks compile times across some common crates over all supported compiler versions, with different hardware (2, 4, 8, 16 cores). This used to be https://arewefastyet.rs but the domain expired.

https://arewefastyet.rs/ see benchmark

You can check incremental compile times on http://arewefastyet.rs. Choose one compile mode (Debug OR Release, preferably Debug), one hardware config (4 cores let's say) and both profile modes (Clean, Incremental).

Compile times in rustc have been steadily improving with time, as shown here - https://arewefastyet.rs.

Every release doesn't make every workload faster, but over a long time horizon, the effect is clear. Rust 1.34 was released in April 2019 and since then many crates have become 33-50% faster to compile, depending on the hardware and the compiler mode (clean/incremental, check/debug/release).

Interestingly, the speedup mentioned in OP won't show up in these charts because that's a change on macOS and these benchmarks were recorded on Linux.

What is expected to be a gamechanger is the release of cranelift in 2021 or 2022. It's an alternate debug backend that promises much faster debug builds.

Yes plenty of effort goes into making Rust compilation faster, see https://arewefastyet.rs/, its FAQ, and some easy internet searches.

Thanks for your work on arewefastyet.rs, I was about to post a link to it haha

I implemented something similar. Deserialising a comma separated strings into a struct - example. Hope that helps!

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!