cl-cuda
paip-lisp
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MIT License | MIT License |
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cl-cuda
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Why Lisp? (2015)
> You can write a lot of macrology to get around it, but there's a point where you want actual compiler writers to be doing this
this is not the job of compiler writers (although writing macros is akin to writing a compiler but i do not think that this is what you mean). in julia the numerical programming packages are not part of the standard library and a lot of it is wrappers around C++ code especially when the drivers to the underlining hardware are closed-source [0]. also here is the similar library in common lisp [1]
[0] https://github.com/JuliaGPU/CUDA.jl
[1] https://github.com/takagi/cl-cuda
- Fast and Elegant Clojure: Idiomatic Clojure without sacrificing performance
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Hacker News top posts: Aug 14, 2021
A Common Lisp Library to Use Nvidia CUDA\ (0 comments)
- A Common Lisp Library to Use Nvidia CUDA
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Machine Learning in Lisp
Personally, I've been relying on the stream-based method using py4cl/2, mostly because I did not - and perhaps do not - have the knowledge and time to dig into the CFFI based method. The limitation is that this would get you less than 10000 python interactions per second. That is sufficient if you will be running a long running python task - and I have successfully run trivial ML programs using it, but any intensive array processing gets in the way. For this later task, there are a few emerging libraries like numcl and array-operations without SIMD (yet), and numericals using SIMD. For reasons mentioned on the readme, I recently cooked up dense-arrays. This has interchangeable backends and can also use cl-cuda. But barring that, the developer overhead of actually setting up native-CFFI ecosystem is still too high, and I'm back to py4cl/2 for tasks beyond array processing.
paip-lisp
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Ask HN: Guide for Implementing Common Lisp
PAIP by Peter Norvig, Chapter 23, Compiling Lisp
https://github.com/norvig/paip-lisp/blob/main/docs/chapter23...
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The Meeting of the Minds That Launched AI
Emacs is so much more than a text editor! But I need to stay on topic...
I believe your assessment of LISP (and therefore of MacArthy)'s impact on AI to be unfair. Just a few days ago https://github.com/norvig/paip-lisp was discussed on this site, for example.
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Towards a New SymPy
Sounds like a great project idea to make a toy demo of this direction you'd like to see. Maybe comparable to https://github.com/norvig/paip-lisp/blob/main/docs/chapter15... and https://github.com/norvig/paip-lisp/blob/main/docs/chapter8.... which are a few hundred lines of Lisp each, but do enough to be interesting.
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A few newbie questions about lisp
You could look into Paradigms of AI Programming by Peter Norvig which might interest you regardless of Lisp content.
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Mathematical paradigm?
Lisp has great power, examine PAIP, part II chapters 7 and 8.
- Peter Norvig – Paradigms of AI Programming Case Studies in Common Lisp
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Evidence that GPT-4 has a level of understanding
A computer running Prolog reasons, and that only requires a couple of pages of code. So it seems feasible that the network could have learned some ability to reason within its network.
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Conversation with Larry Masinter about Standardizing Common Lisp
IMHO it's because lisp shines to manipulate symbols whereas the current AI trend is crunching matrices.
When AI was about building grammars, trees, developing expert systems builds rules etc. symbol manipulation was king. Look at PAIP for some examples: https://github.com/norvig/paip-lisp
This paradigm has changed.
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A lispy book on databases
Origen: Conversación con Bing, 4/4/2023(1) gigamonkey/monkeylib-binary-data - GitHub. https://github.com/gigamonkey/monkeylib-binary-data Con acceso 4/4/2023. (2) paip-lisp/chapter4.md at main · norvig/paip-lisp · GitHub. https://github.com/norvig/paip-lisp/blob/main/docs/chapter4.md Con acceso 4/4/2023. (3) bibliography.md · GitHub. https://gist.github.com/gigamonkey/6151820 Con acceso 4/4/2023.
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A Retrospective on Paradigms of AI Programming (2002)
If anyone is interested PAIP is downloadable at https://github.com/norvig/paip-lisp
What are some alternatives?
numcl - Numpy clone in Common Lisp
mal - mal - Make a Lisp
criterium - Benchmarking library for clojure
30-days-of-elixir - A walk through the Elixir language in 30 exercises.
numericals - CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental]
Crafting Interpreters - Repository for the book "Crafting Interpreters"
py4cl - Call python from Common Lisp
coalton - Coalton is an efficient, statically typed functional programming language that supercharges Common Lisp.
hash-array-mapped-trie - A hash array mapped trie implementation in c.
picolisp-by-example - The source code of the free book "PicoLisp by Example"
rewrite - Automated mass refactoring of source code.
slime - The Superior Lisp Interaction Mode for Emacs