compiler VS compiler-explorer

Wow! Thank you for your hard work. I use python for all experimental work so this would speed up my scripting work, such as processing data from API calls or filesystem.

I wrote a simple toy JIT for a Javascript-like language. It might be useful for others to learn from because it's so simply written and not complicated. I do lazy patching of callsites, I haven't got anywhere near as advanced as tracing or copy-and-patching. Much of the code I wrote for this JIT was written in Python and ported to C. The Java Virtual Machine has a template interpreter which is interesting to research.

I haven't got around to encoding amd64 x86_64 instructions as bitmasks yet, so I've hardcoded it.

[1]: https://github.com/samsquire/compiler

Thank you for this article.

I'm a beginner to programming language implementation and design but here's what I learned. But what I want to do this with this comment I want to encourage you to start work on your programming language and just "Do Something©", Anything! You might have always dreamed to create a programming language. You can indeed try that! Have faith that you can do something, even if it's simple or incomplete, at least you learned something and got another skill.

I don't want to be trapped by the idea that building your own programming language is impossibly difficult and that it will never be used so what's the point.

It's so worthwhile.

You can still do something! Effort doesn't have to be wasted! Go and try write a simple virtual machine: it's just a for loop over instructions that manipulate memory. I wrote a non-bytecode compiler, which just uses List for instructions and HashMap for instruction arguments.

Andrew Kling built a browser and operating system and Terry Davis built an operating system. They encourage that someone can in fact learn a lot and do a lot.

I don't want to endlessy design things OR only write implementations. I think you can write lots of ideas down AND spend time implementing things and getting your keyboard busy.

I wrote this incomplete JIT compiler in C which has a simple nondesigned frontend that resembles Javascript. ANF is my intermediate representation.

https://github.com/samsquire/compiler

I wrote a multithreaded imaginary assembly language that sends integers between threads through mailboxes but nowhere near LMAX Disruptor performance.

I think you should avoid spending too much time on your parser or lexer, use the Kaledeiscope LLVM tutorial to learn how to write recursive descent parsers and move onto code generation. I did mine with switch statements. The more you actually write parsers the easier it gets, but at first when you have no clue, you CAN just read someone else's implementation of it. Understand it, then write your own to your own design. if you get Analysis paralysis and worry about making a mistake or unoptimal decision and that prevents you from doing something suboptimal but actually do something.

I rushed through my compiler to get to the code generation step because my goal was code generation.

My dream: parallel and concurrent language that combines threads and coroutines with efficient interthread communication similar to LMAX Disruptor and allows writing of efficient pipelines that are serialisable like Temporal.io.

Thanks for this.

I started a basic toy JIT compiler for a language that looks similar to JavaScript. It is incomplete.

https://github.com/samsquire/compiler

With these kinds of projects there is a lot of work to be done and I feel it's difficult to get started reading a codebase for a JIT compiler or gcc or LLVM.

https://github.com/samsquire/compiler

It's a toy and incomplete but I've worked on compiling MOV and ADD instructions.

On thing you can do it implement a JIT compiler.

Here's Martin Jacob's code to execute arbitrary memory:

https://gist.github.com/martinjacobd/3ee56f3c7b7ce621034ec3e...

Since your C program is already in memory, you have access to the C standard library and don't have to worry about linking or object formats :-) but you'll have to worry about parameter passing and FFI.

My JIT compiler based on this idea is here https://github.com/samsquire/compiler but it is incomplete.

This is interesting, thank you.

I really should learn from BEAM and the OTP and learn Erlang. I get the feeling it's super robust and reliable and low maintenance. I wrote a userspace multithreaded scheduler which distributes N lightweight threads to M kernel threads.

https://github.com/samsquire/preemptible-thread

I recently wrote a JIT compiler and got lazy compilation of machine code working and I'm nowhere near beginning optimisation

https://github.com/samsquire/compiler

How do you write robust software, that doesn't crash when something unexpected goes on?

I looked at sozo https://github.com/sozu-proxy/sozu

and I'm thinking how to create something that just stays up and running regardless.

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!