ngn-k-tutorial
dex-lang
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ngn-k-tutorial
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Thinking in an Array Language
Complain about the language or documentation, but array language communities are absolutely friendly to outsiders! This tutorial lists some active forums, give them a try:
https://github.com/razetime/ngn-k-tutorial/tree/main?tab=rea...
Also, have to shout out the APL Orchard, where Adám will give any visitor a personal tutorial: https://chat.stackexchange.com/rooms/52405/the-apl-orchard
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APL: An Array Oriented Programming Language (2018)
To add to the list, this one is pretty good;
https://github.com/razetime/ngn-k-tutorial
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rando Q vs J thoughts | Locklin on science
If you like APL, then you probably want to try K, which is an ASCII-only array language with a focus on guided minimalism. For an open source K you can try ngn/k, which has a tutorial.
- Thinking in an array language
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Ngn/k (free K implementation)
Razetime's matmul refactoring is brilliant: https://github.com/razetime/ngn-k-tutorial/blob/main/c-think...
Finally, some nice examples of k's concision:
qs:{$[2>#?x;x;,/qs'x@&'~\:x<*1?x]} / Quicksort
- An ngn/k Tutorial
dex-lang
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Thinking in an Array Language
A really nice approach to this I've seen recently is Google's research on [Dex](https://github.com/google-research/dex-lang).
- Function Composition in Programming Languages – Conor Hoekstra – CppNorth 2023 [video]
- Dex Lang: Research language for array processing in the Haskell/ML family
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[D] Have their been any attempts to create a programming language specifically for machine learning?
Dex
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[D] PyTorch 2.0 Announcement
Have you tried Dex? https://github.com/google-research/dex-lang It is in a relatively early stage, but it is exploring some interesting parts of the design space.
- Mangle, a programming language for deductive database programming
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Looking for languages that combine algebraic effects with parallel execution
I think [Dex](https://github.com/google-research/dex-lang) might be along the lines of what you're looking for, although its focus is on SIMD GPU-style parallelism rather than thread-level parallelism.
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“Why I still recommend Julia”
Dex proves indexing correctness without a full dependent type system, including loops.
See: https://github.com/google-research/dex-lang/pull/969
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Haskell for Artificial Intelligence?
In case you want to see one research direction that's combining practical machine learning and functional programming, one of the authors of JAX (and the main author of its predecessor, Autograd) is writing Dex (https://github.com/google-research/dex-lang), a functional language for array processing. The compiler itself is written in Haskell. JAX is one of the most popular libraries for doing a lot of machine learning these days, along with Tensorflow and PyTorch. You might also want to see the bug in the JAX repo about adding Haskell support, for some context: https://github.com/google/jax/issues/185
What are some alternatives?
b-decoded - arthur whitney's b interpreter translated into a more traditional flavor of C
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
kona - Open-source implementation of the K programming language
futhark - :boom::computer::boom: A data-parallel functional programming language
april - The APL programming language (a subset thereof) compiling to Common Lisp.
julia - The Julia Programming Language
kdb - kdb+ Working Group from FINOS Data Technologies program
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
rsbqn - An embeddable BQN virtual machine in rust. Stay tuned!
hasktorch - Tensors and neural networks in Haskell
ok - An open-source interpreter for the K5 programming language.
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