Modifying the ABI of a function requires being able to track down all of the call-sites of the function, which is less trivial than you might assume. ABI concerns also tend to baked in relatively early in the optimization pipeline because you just simply can't get the ABI wrong, and I can think of several instances where the ABI decision causes missed optimizations.

There is also the other issue that a good algorithm for optimizing a problem like register allocation tends to be super-linear (e.g., quadratic), and if you shift the model from "allocate on a per-function basis" to "allocate all functions", the N in the O(N²) goes from "size of function" to "size of program," which is now suddenly a lot more compiler time spent for very modest gains. If register spilling across a function call is a noticeable component of runtime, then you're probably better off inlining that function in the first place!

This is already done in the form of deciding whether or not to inline a function.

Yeah, that's what MSVC and GCC did on x86, called "custom calling conventions" on MSVC and the regparm attribute on GCC.

All of these were dropped on x64, on x64 (and ARM) you get standard calling conventions for just about everything with proper unwind tables for functions.

It doesn't really "cheat" on the registers unless it inlines a function entirely. LLVM has support for custom calling conventions and pragmas to specify them, this is used by GHC on Haskell and other things, but it's practically unheard of in "normal" C/C++ code.

If it were practical and if there were significant performance benefits (on modern heavyweight CPUs) to tailoring the calling convention on a per-function basis, I'd expect to see it done in optimising JIT engines like Java HotSpot. As far as I know, they don't bother.

I'm no expert but I suspect jcranmer's comment has it right that you end up doing cross-function register-allocation while foregoing the other benefits of just inlining. I also suspect the payoff would be minimal on modern heavyweight hardware. I can see it making more of a difference on a very minimal embedded processor, or if optimising for the smallest binary possible.

Hand-optimized assembly tends to be ephemeral. My codebase constantly changes, which means hand-written assembly had to be redone.

It's rarely worth the effort.

There a lot of juice in improving the data structures that a compiler cannot do.

With hand-written assembly, you can (with effort and care) ensure that the code runs in constant time and doesn’t leak any information through side channels (such as which memory or cache addresses it accesses). That’s important for most encryption code. It’s difficult to ensure constant time execution in pure Rust (or C, or most high level languages in general) because you can’t tell if some future compiler optimization will break your attempts at constant-time code.

An optimizer is trying to balance between compile time, runtime speed, and code size, and most optimizations will win you one axis at the cost of one or both of the other axes. (The rare optimizations that win on all 3 are already all implemented in the compiler.) Compiler developer time is also a scarce resource; I know of so many more optimizations I could implement, but without demonstrable code that would actually benefit, it's not a good use of my time to implement them. Compilers tune this balance by making lots of heuristic decisions, and these heuristics are tuned by large benchmarks, which often times involve a lot of flat code profiles (i.e., no code is worth spending a lot of time really nailing down the best code layout).

One of the advantages of hand-written assembly is that you get to opt out of the compiler heuristics and commit to being able to spend the time to optimize the one bit of code that you know is really important for runtime as perfectly as you want, instead of relying on the compiler to get it close enough to perfect before it exhausts its budget of caring about optimizing it.

1. Better memory locality by knowing what you load and when, exactly.

2. The ability to "cheat" on calling conventions.

3. The ability for techniques like threaded code, and in general, better cache-awareness.

4. Less mov's.

5. Guaranteeing no spilling in important loops.

6. Compilers don't do well with flags registers and you can't read/write them in high level languages. You're hoping your `if (result < a) { carry = 1; }` becomes a direct flag test. Especially important in bignum, you can't really utilise adcx/adox directly from high-level code.

7. Hot/cold layout without PGO. Yes PGO is good but sometimes you know better and PGO isn't very suitable for "configurable" code.

8. Computed goto. See https://github.com/python/cpython/issues/128563 , who doesn't like 10% free performance?

9. Exploiting uninitialised memory for classic party tricks like not initialising a buffer fully (let's say you have a library function with a return buffer. You don't want dynamic allocations for some reason. You can simulate this with a pointer return into a let's say a static 4KB buffer and a count return, you only initialise it until the count. Caller has the responsibility not to overread.)

usually with Rust impactful savings come from writing the Rust differently, not from doing hand-written assembly instead.

See stuff like https://davidlattimore.github.io/posts/2025/09/02/rustforge-...

This doesn't mean Rust is near perfect, it's just that your first move should be "how do I make the Rust better" and not "I need to drop into asm."

Entirely situation and application specific. Just like with every other language.

As one example, LLVM still routinely does dumb stuff like this: https://github.com/llvm/llvm-project/issues/53348

Regarding ABI, calee-saved registers also often result in useless data shuffling and prevent the compiler from using them for argument/result passing.

Any “Multimedia Extensions” or streaming or whatever beyond what’s available past a 486.

Rust has autovectorization, but a developer knows their algorithms best.

Also AES-NI vs software is no contest.

When people talk about out coding ‘to the metal’ you have to consider what ‘the metal’ provides

JIT compilers are essentially producing self-modifying programs (or, indeed, dynamically loaded libraries).

Dynamic languages, like Common Lisp, where things can be redefined at run time likely require modification of running code to achieve high efficiency (the alternative is to just leave a general mechanism in place and accept the runtime overhead and loss of optimization opportunities from that.)

That depends how far in advance of running the code you're modifying it. You could see a JIT compiler as an extreme type of SMC. Or a Monero miner - its hashing algorithm relies on running randomly generated programs.