clingo
egg
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clingo
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Learn Datalog Today
One of the easiest to get started on Datalog in my opinion is really clingo https://potassco.org/clingo/ , which can be pip installed and has python bindings. Answer Set Programming goes beyond datalog, but it holds datalog semantics as a sublanguage. It is unfortunate this is not well advertised.
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Modern SAT solvers: fast, neat and underused (2018)
Love this article and the push to build awareness of what modern SAT solvers can do.
The thing it misses, though, is that there are higher level abstractions that are far more accessible than SAT. If I were teaching a course on this, I would start with either Answer Set Programming or Satisfiability Modulo Theories (SMT). The most widely used solvers for those are clingo [0] and Z3 [1]:
With ASP, you write in a much clearer Prolog-like syntax that does not require nearly as much encoding effort as your typical SAT problem. Z3 is similar -- you can code up problems in a simple Python API, or write them in the smtlib language.
Both of these make it easy to add various types of optimization, constraints, etc. to your problem, and they're much better as modeling languages than straight SAT. Underneath, they have solvers that leverage all the modern CDCL tricks.
We wrote up a paper [2] on how to formulate a modern dependency solver in ASP; it's helped tremendously for adding new types of features like options, variants, and complex compiler/arch dependencies to Spack [3]. You could not get good solutions to some of these problems without a capable and expressive solver.
[0] https://github.com/potassco/clingo
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Ask HN: What is new in Algorithms / Data Structures these days?
Answer Set Programming is an incredibly powerful tool to declaratively solve combinatorial problems. Clingo is one of the best open source implementations in my opinion: https://github.com/potassco/clingo
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/
What are some alternatives?
ezno - A JavaScript compiler and TypeScript checker written in Rust with a focus on static analysis and runtime performance
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.
Decider - An Open Source .Net Constraint Programming Solver
Symbolics.jl - Symbolic programming for the next generation of numerical software
libclc - Cache Line Container - C11
Catlab.jl - A framework for applied category theory in the Julia language
pub - The pub command line tool
Dagger.jl - A framework for out-of-core and parallel execution
highfleet-ship-opt - A c/c++ module and python extensions for automatic optimization of Highfleet ship modules. Try it live at https://hfopt.jodavaho.io
glow - Compiler for Neural Network hardware accelerators
egglog - egraphs + datalog!
StaticArrays.jl - Statically sized arrays for Julia