zigenesis
qbe-rs
| zigenesis | qbe-rs | |
|---|---|---|
| 1 | 29 | |
| 9 | 66 | |
| - | - | |
| 10.0 | 3.3 | |
| over 1 year ago | 8 months ago | |
| Zig | Rust | |
| - | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
zigenesis
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Smallest possible self-hosting zig compiler
First, I recently started a new project in this area that might interest you: https://github.com/bettertools/zigenesis
qbe-rs
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Odin Programming Language
> I think it uses a different backend than LLVM
harec uses https://c9x.me/compile/
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Frontend for GCC?
Have you considered QBE?
- QBE – Compiler Back End
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What do C programmers think of the Zig language in 2023?
I really hope other new projects (like QBE) can really grow and become widely used
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Toy C compiler, worth having an IR stage?
I really liked targetting QBE (https://c9x.me/compile/) as an IR, as it gave me lots of back-end optimisations for free 😊.
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C or LLVM for a fast backend?
There is: QBE.
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A whirlwind tour of the LLVM optimizer
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
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Made my first LLVM front-end… Now what?
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.
- Best book on writing an optimizing compiler (inlining, types, abstract interpretation)?
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Rust port of B3 from WebKit, LLVM-like backend
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.
What are some alternatives?
fngi - a readable language that grows from the silicon
ubpf - Userspace eBPF VM
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
mir - A lightweight JIT compiler based on MIR (Medium Internal Representation) and C11 JIT compiler and interpreter based on MIR
minivm - A VM That is Dynamic and Fast
c4 - C in four functions
well - The Future of Assembly Language. https://wellang.github.io/well/
wasmtime - A fast and secure runtime for WebAssembly
Befunge - lang befunge 93 fast
Som - Parser, code model, navigable browser and VM for the SOM Smalltalk dialect
cproc - C11 compiler (mirror)
asmjit - Low-latency machine code generation