movfuscator VS compiler-explorer

Everything can be reduced to assignments. https://github.com/xoreaxeaxeax/movfuscator

However, the movfuscator as implemented does still require a sigaction(2) syscall to set up a signal handler, under the justifications that "it is not actually part of the program" and that "if we were in ring 0, we wouldn't need help from the kernel" [0]. However, the latter part seems a little dubious to me: without the help of the kernel running non-MOV instructions, you'd never be able to escape from 16-bit real mode into 32-bit protected mode, since you wouldn't be able to load a valid GDT with the LGDT instruction (as far as I am aware).

[0] https://github.com/xoreaxeaxeax/movfuscator/blob/90a49f31219...

I _think_ the idea is thinking of an "interface" as "something that you use as a way to interact with something from outside an abstraction". I'd summarize their argument as reasoning that if the goal of an abstraction is to avoid having to care about the internal details of something, an interface is a way to expose a subset of ways to interact with it, and the more you expand it, the more it exposes the internals of the thing being abstracted. I don't think they necessarily mean this only in terms of programming, but you could apply this argument to a programming language interface; if you use an interface for interacting with something instead of its direct functionality, each additional method you add to the interface exposes more details of the inner value, which makes it less of an abstraction.

Assuming my interpretation is correct, I'm not sure I totally buy this argument because there doesn't seem to be an obvious way to define the "size" of an interface where it holds true. The naive way to define the size would be number of methods, but I'd argue that methods can vary so much in terms of the amount of cognitive overhead they "expose" to the user that it's not very meaningful. Consider the Movfuscator compiler[0], which compiles code into binaries only using MOV x86 instructions because it happens to be Turing complete; as complex as it might be to learn x86 assembly as a whole and start writing programs directly in it, I'm dubious that trying to do so only with MOV would somehow be easier. Put another way, an x86 instruction set that only contains the MOV instruction is not a "stronger" abstraction than the actual one because it _introduces_ complexity that doesn't exist in the original. Does adding an ADD instruction alongside MOV increase the strength of the abstraction, or weaken it? I don't think there's an answer that we'd immediately all agree on for this sort of thing.

Ultimately, I think trying to measure interfaces through the number of methods they expose is similar to trying to measure code by the number of lines in it; while there are some extreme cases where we'd likely all agree (e.g. for a fizzbuzz implementation, having 10 lines of code is probably better than thousands of lines of code[1]), we can't really come up with a good objective metric because the "target" number is based on the complexity of what you're trying to define, and we don't have a way of quantifying that complexity. I think the ideas here are still super interesting though, not because they have definitive right or wrong answers, but because thinking about stuff like this overall improves one's ability to write good software for usage by other programmers.

[0]: https://github.com/xoreaxeaxeax/movfuscator

The mov instruction in x86-64 is Turing complete. Someone even made a C compiler using only mov.

Are you sure they didn't use the MOVFUSCATOR?

Yep. In fact you can reduce everything to just one simple assembly instruction.

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!