AnyAny
compiler-explorer
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AnyAny | compiler-explorer | |
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22 | 188 | |
421 | 15,106 | |
- | 1.9% | |
6.2 | 9.9 | |
14 days ago | 3 days ago | |
C++ | TypeScript | |
Apache License 2.0 | BSD 2-clause "Simplified" License |
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AnyAny
- DynaMix 2.0.0 Released
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rust-like traits on plain C++ with short macro (type erasure actually)
https://github.com/kelbon/AnyAny trait(add, void(int), self.add(args...));
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Static Interfaces, concepts vs de-virtualisation?
i dont know what he means, but with this type erasure library you can have non virtual interface and still use dynamic polymorphism with those types, so you dont need choose *do i need to do this type polymorphic* etc
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[C++23] constexpr std::function in 40 LOC (simplified) powered by constexpr std::unique_ptr
There are also invoking from tuple and curring (just an example of technique)https://github.com/kelbon/AnyAny/blob/main/examples/functional_paradigm.hpp
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A call to action: Think seriously about “safety”; then do something sensible about it -> Bjarne Stroustrup
As for my example containers: https://github.com/kelbon/AnyAny/blob/main/include/data_parallel_vector.hpp
- C++ Polymorphism Without Inheritance Using Glaze
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С++20 library for high-performance polymorphic types usage
variant_swarm - container which behaves as set of std::variant, but with much faster visit operation and operation for getting view to all values of type T. It short, it just stores all types separatelly and supports operations visit, view, also you can change underlying containers for Ts..., it is std::vector by default https://github.com/kelbon/AnyAny/blob/main/include/variant_swarm.hpp
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I wrote multidispatching(runtime overload resolution) in C++ (and its not std::variant)
Its part of my library for working with polymorphic types.
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I wrote a library that emulates dyn traits from Rust in C++
Good idea selling Rust from behind enemy lines soldier! My god, your readme doesn't even mention Rust, wonderful!
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Using final in C++ to improve performance
https://github.com/kelbon/AnyAny here you can see how it implemented, for example
compiler-explorer
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C++ Insights – See your source code with the eyes of a compiler
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.
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Ask HN: How can I learn about performance optimization?
[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.
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Managing mutable data in Elixir with Rust
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:
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Free MIT Course: Performance Engineering of Software Systems
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/
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Verifying Rust Zeroize with Assembly...including portable SIMD
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.
- 4B If Statements
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Operator precedence doubt
Play around with it in godbolt if you're really curious: https://godbolt.org/
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Cant Use Vectors in VSCode
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!
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Is the runtime stack (memory) and the call stack the same thing?
Try stuff out at godbolt.org . See what happens if you switch to arm .vs. x86. Try -O0 and -O3.
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Performance difference between obj.function(...) and function(obj, ...) ?
That sounds weird, the calls should produce identical machine code if all other factors are equal. You can compare the generated assembly code at Compiler Explorer. And yes, be sure to build with optimizations turned on.
What are some alternatives?
tolc - A bindings compiler for C++
C++ Format - A modern formatting library
dyno - Runtime polymorphism done right
rust - Empowering everyone to build reliable and efficient software.
Kalman - Kalman Filter
format-benchmark - A collection of formatting benchmarks
kelcoro - C++20 coroutine library
papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management
ReactivePlusPlus - Implementation of async observable/observer (Reactive Programming) in C++ with care about performance and templates in mind in ReactiveX approach
rustc_codegen_gcc - libgccjit AOT codegen for rustc
tinyformat - Minimal, type safe printf replacement library for C++
firejail - Linux namespaces and seccomp-bpf sandbox