egg
lean4
egg | lean4 | |
---|---|---|
25 | 55 | |
1,239 | 3,763 | |
2.7% | 3.1% | |
6.8 | 9.9 | |
10 days ago | 4 days ago | |
Rust | Lean | |
MIT License | Apache License 2.0 |
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.
egg
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An Introduction to Graph Theory
Maybe program optimization?
https://egraphs-good.github.io/
- The E-graph extraction problem is NP-complete
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What is the state of the art for creating domain-specific languages (DSLs) with Rust?
For semantic analyzers, check out egg and egglog. They're custom data structures for representing compiler rewrite rules in a non-destructive way.
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Ask HN: What is new in Algorithms / Data Structures these days?
E-graphs are pretty awesome, and worth keeping in your back pocket. They're like union-find structures, except they also maintain congruence relations (i.e. if `x` and `y` are in the same set, then `f(x)` and `f(y)` must likewise be in the same set).
https://egraphs-good.github.io/
(Incidentally, union-find structures are also great to know about. But they're not exactly "new".)
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What are the current hot topics in type theory and static analysis?
I would add that Equality saturation/E-graphs has become quite a hot topic recently, since their POPL21 paper, with workshops dedicated to applications of e-graphs. They have even recently been added to Cranelift as an IR for optimizations.
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Compiler Optimizations Are Hard Because They Forget
Egraphs solve the rewrite ordering problem quite nicely. https://egraphs-good.github.io/
Note that one solution to this problem is to use equality saturation (which, coincidentally, has a great implementation in rust!).
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Modularity in IR representation and modification
Have you thought about trying to parallelize e-graphs? This way you can do a bunch of rewrite rules in parallel and then extract your desired graph at the end instead of having conflicts.
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Any recommendations for good resources that show how algorithms and data structures are converted into fpga circuits
I think the equality saturation papers are a good start. A good start is egg. They have a presentation, a research paper and code you can play with. I think ultimately you want to translate arithmetic operations into logical operation that can be understood by the fpga. So I think it would be good to research how adders and multipliers are implemented in logic and ultimately include equalities between adders/multipliers with their logical counterpart. Note the this translation also depends on the representations of your numbers and their bit width.
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Strategies for doing symbolic integration algorithmically
For rewriting, you may also find interesing equality saturation: https://egraphs-good.github.io/
lean4
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The Fermat's Last Theorem Project
Lean is free and open source and nothing to do with MS. Check out https://lean-lang.org/ and https://github.com/leanprover/lean4 -- no mention of MS or MSR (where de Moura was where he developed Lean 3 and started on Lean 4).
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Dafny is a verification-aware programming language
Recently replaced by Lean, though.
https://github.com/cedar-policy/cedar-spec
https://lean-lang.org
- The Mechanics of Proof
- Natural Deduction in Logic (2015)
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The Wizardry Frontier
Nice read! Rust has pushed, and will continue to push, the limits of practical, bare metal, memory safe languages. And it's interesting to think about what's next, maybe eventually there will be some form of practical theorem proving "for the masses". Lean 4 looks great and has potential, but it's still mostly a language for mathematicians. There has been some research on AI constructed proofs, which could be the best of both worlds because then the type checker can verify that the AI generated code/proof is indeed correct. Tools like Kani are also a step forward in program correctness.
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Lean4 helped Terence Tao discover a small bug in his recent paper
Yeah, I believe they said intend for it to be used as a general purpose programming language. I used it to complete Advent of Code last year.
There are some really interesting features for general purpose programming in there. For example: you can code updates to arrays in a functional style (change a value, get a new array back), but if the refcount is 1, it updates in place. This works for inductive types and structures, too. So I was able to efficiently use C-style arrays (O(1) update/lookup) while writing functional code. (paper: https://arxiv.org/abs/1908.05647 )
Another interesting feature is that the "do" blocks include mutable variables and for loops (with continue / break / return), that gets compiled down to monad operations. (paper: https://dl.acm.org/doi/10.1145/3547640 )
And I'm impressed that you can add to the syntax of the language, in the same way that the language is implemented, and then use that syntax in the next line of code. (paper: https://lmcs.episciences.org/9362/pdf ). There is an example in the source repository that adds and then uses a JSX-like syntax. (https://github.com/leanprover/lean4/blob/master/tests/playgr... )
- A Linguagem Lua completa 30 anos!
- Lean 4.0
- Lean 4.0.0, first official lean4 release
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Looking to start a new community for people who want to use code for everything
My latest inspiration to use code to a) replace my video editor, b) learn the basics of EDM production and c) understand a few topics in higher maths. This might sound very strange given there are specialised tools for these jobs. There's iMovie / Adobe Premier for video, there's GarageBand and FL studio for music and old good pen and pencil for math proofs. But these tools have three big limitations. First they have a lot of idiosyncratic learning, you have to spend quite some time getting used to these tools and my experience is that this time is quite upsetting. In contrast, you only have to learn to code one, maybe spend a few hours getting used to the syntax of another language. I'm not sure if that's true for most people but it was true for me using the tools mentioned above and wanted a place to discuss and see other people ideas and experiments. The second issue is that all these custom-made tools, are not composing easily. I can't search for all math proofs that used a single theorem. I can't create a plugin for iMovie and apply it to all my videos. I can't pick easily pick a rhythm from the internet and build upon for fun. There's also the issue of costs and version control, all tools I'm using today are open source and my work is stored in my repositories. This way I can create branches and test my ideas and I'm also confident that I can work in these projects in years.
What are some alternatives?
prose - Microsoft Program Synthesis using Examples SDK is a framework of technologies for the automatic generation of programs from input-output examples. This repo includes samples and sample data for the Microsoft Program Synthesis using Example SDK.
z3_tutorial - Jupyter notebooks for tutorial on the Z3 SMT solver
Symbolics.jl - Symbolic programming for the next generation of numerical software
coq - Coq is a formal proof management system. It provides a formal language to write mathematical definitions, executable algorithms and theorems together with an environment for semi-interactive development of machine-checked proofs.
Catlab.jl - A framework for applied category theory in the Julia language
Agda - Agda is a dependently typed programming language / interactive theorem prover.
Dagger.jl - A framework for out-of-core and parallel execution
ATS-Postiats - ATS2: Unleashing the Potentials of Types and Templates
glow - Compiler for Neural Network hardware accelerators
ts-sql - A SQL database implemented purely in TypeScript type annotations.
StaticArrays.jl - Statically sized arrays for Julia
roc - A fast, friendly, functional language. Work in progress!