simplelanguage
qbe-rs
simplelanguage | qbe-rs | |
---|---|---|
6 | 30 | |
594 | 66 | |
0.8% | - | |
4.8 | 3.3 | |
7 months ago | 8 months ago | |
Java | Rust | |
Universal Permissive License v1.0 | GNU General Public License v3.0 or later |
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simplelanguage
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Dada, an Experiement by the Creators of Rust
That sort of stuff is easy to do with Truffle (which, ironically, lets you define a language using what they call the "truffle dsl").
The SimpleLanguage tutorial language has a bigint style number scheme with efficient optimization:
https://github.com/graalvm/simplelanguage/blob/master/langua...
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Apple releases Pkl – onfiguration as code language
Truffle has no opinion on how you parse the sources. It cares about how you execute them from an intermediate Truffle guided representation produced by the parser.
In other words antlr and truffle are a great fit. We even use this pairing for our example language simplelanguage.
https://github.com/graalvm/simplelanguage
- PL Scaffolding project?
- Ask HN: Recommendation for general purpose JIT compiler
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GraalVM 22.1: Developer experience improvements, Apple Silicon builds, and more
Do you have any feedback on how we could improve the docs? If so, please let us know!
I believe the easiest way to start a new Truffle language implementation is to fork SimpleLanguage [1] and turn it into your language. Did you try to do that?
[1] https://github.com/graalvm/simplelanguage
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Where would you recommend starting if I want to make my own programming language?
Finally, I would suggest you to take a look at the Truffle/GraalVM ecosystem(https://www.graalvm.org/graalvm-as-a-platform/language-implementation-framework/). The documentation is not exactly very elaborate, but a few good resources are Mumbler(http://cesquivias.github.io/blog/2014/10/13/writing-a-language-in-truffle-part-1-a-simple-slow-interpreter/#mumbler-language), SimpleLanguage(https://github.com/graalvm/simplelanguage), and (https://www.endoflineblog.com/graal-truffle-tutorial-part-4-parsing-and-the-trufflelanguage-class).
qbe-rs
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CBMC: C bounded model checker. (2021)
Another problem with LLVM I’ve heard about is that it’s intermediate language or API or something is a moving, informally-specified target. People who know LLVM internals might weigh in on that claim. If true, it’s actually easier to target C or a subset of Rust just because it’s static and well-understood.
Two projects sought to mitigate these issues by going in different directions. One was a compiler backend that aimed to be easy to learn with well-specified IL. The other aimed to formalize LLVM’s IL.
http://c9x.me/compile/
https://github.com/AliveToolkit/alive2
There have also been typed, assembly languages to support verification from groups like FLINT. One can also compile language-specific analysis with a certified to LLVM IL compiler. Integrating pieces from different languages can have risks. That (IIRC) is being mitigated by people doing secure, abstract compilation.
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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)?
What are some alternatives?
graalvm-kotlin-native-image-sample - Example project showing how to build a native, static executable from a Kotlin project using GraalVM
ubpf - Userspace eBPF VM
Som - Parser, code model, navigable browser and VM for the SOM Smalltalk dialect
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
jet - CLI to transform between JSON, EDN, YAML and Transit using Clojure
c4 - C in four functions
clj-kondo - Static analyzer and linter for Clojure code that sparks joy
well - The Future of Assembly Language. https://wellang.github.io/well/
wasmtime - A fast and secure runtime for WebAssembly