asmjit VS qbe-rs

Some other instruction sets in some JSON: https://github.com/asmjit/asmjit/tree/master/db

The attentive reader may notice that this code is from a third-party library. So, we didn't want to include it in the article at first. However, we found something interesting. In 2017, somebody opened an issue in the asmjit project: the GCC 7.2 compiler issued a warning to the code above. The project authors fixed it:

You can use something like https://asmjit.com/ to generate and call x64 code at runtime.

But an easy to create a JIT would be to use https://github.com/asmjit/asmjit, which is used in RPCS3.

You could go the way of https://asmjit.com (or forth) and make it your assembler DSL on top of the low-level call.

But if you're willing to get closer to the hardware is https://github.com/bitfunnel/nativejit/ and https://asmjit.com/

https://github.com/asmjit/asmjit is nice. But using a JIT seems like a sledgehammer working around a lacking design.

> I think it uses a different backend than LLVM

harec uses https://c9x.me/compile/

Have you considered QBE?

I really hope other new projects (like QBE) can really grow and become widely used

I really liked targetting QBE (https://c9x.me/compile/) as an IR, as it gave me lots of back-end optimisations for free 😊.

There is: QBE.

You might be underestimating the accuracy of the CPU models LLVM uses.

For x86, the same data the code generator uses drives llvm-mca[1], which given a loop body can tell you the throughput, latency, and microarchitectural bottlenecks (decoding, ports, dependencies, store forwarding, etc.)—if not always precisely, then still not worse then IACA, the tool written at Intel by people who presumably knew how the CPUs work, unlike LLVM contributors and the rest of us who can only guess and measure. This separately for Haswell, Sandy Bridge, Skylake, etc.; not “x86”.

Now, is this the best model you can get? Not exactly[2], but it’s close enough to not matter. Do we often need machine code to be optimized to that level of detail? Perhaps not[3], and with that in mind you can shave at least a factor of ten off LLVM’s considerable bulk at the cost of 20—30% of performance[4,5]. But if you do want those as well, it seems that the complexity of LLVM is a fair price, or has the right order of magnitude at least.

(Frontend not included, C++ frontend required to bootstrap sold separately, at a similar markup compared to a C-only frontend with somewhat worse ergonomics.)

[1] https://llvm.org/docs/CommandGuide/llvm-mca.html

[2] https://www.uops.info/

[3] https://briancallahan.net/blog/20211010.html

[4] https://c9x.me/compile/

[5] https://drewdevault.com/talks/qbe.html

You can try buildling you own backend like llvm. A good example or starting point is probably QBE since it is extremely small but very functional.

How big is the whole backend? I've heard that it is small but I wanted to compare it to QBE which is around 8 KLoC and it is quite interesting too.