Dagger.jl
egg
Dagger.jl | egg | |
---|---|---|
4 | 25 | |
581 | 1,239 | |
1.7% | 2.7% | |
8.9 | 6.8 | |
4 days ago | 10 days ago | |
Julia | Rust | |
GNU General Public License v3.0 or later | MIT License |
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Dagger.jl
- Dagger: a new way to build CI/CD pipelines
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DTable a new distributed table implementation in Julia using Dagger.jl
Firstly, I'll say that we already have work started to implement out-of-core directly in Dagger: https://github.com/JuliaParallel/Dagger.jl/pull/289.
With that PR in place, it should be possible to define a "storage device" which is backed by a database. I haven't had a chance to actually try this, since the PR still needs quite some work and testing, but it's definitely something on my radar!
- From Julia to Rust
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Cerebras’ New Monster AI Chip Adds 1.4T Transistors
I'm not sure that's necessarily the domain of a low-level package like CUDA.jl though (which I assume you're referring to). That kind of interface is more the domain of higher-level packages like https://github.com/JuliaParallel/Dagger.jl/ and to a lesser extent https://juliagpu.github.io/KernelAbstractions.jl/stable/. Moreover, the jury is still out on whether the built-in Distributed module is an ideal abstraction for every use-case (clusters, heterogeneous compute, etc.)
WRT Nx, my biggest question is how they'll crack the problem of still needing big balls of C++ and the shims everywhere to get acceleration. Creating a compiler that generates efficient GPU or other accelerator code is a massive research project with no clear winners, never mind the challenge of reconciling the very mutation-heavy needs of GPU compute with a mostly immutable language model.
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?
earthly - Super simple build framework with fast, repeatable builds and an instantly familiar syntax – like Dockerfile and Makefile had a baby.
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.
julia - The Julia Programming Language
Symbolics.jl - Symbolic programming for the next generation of numerical software
DuckDB.jl
Catlab.jl - A framework for applied category theory in the Julia language
determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
glow - Compiler for Neural Network hardware accelerators
Metatheory.jl - General purpose algebraic metaprogramming and symbolic computation library for the Julia programming language: E-Graphs & equality saturation, term rewriting and more.
StaticArrays.jl - Statically sized arrays for Julia
JET.jl - An experimental code analyzer for Julia. No need for additional type annotations.