Petalisp
mgl
Petalisp | mgl | |
---|---|---|
17 | 15 | |
425 | 573 | |
- | - | |
8.5 | 3.7 | |
about 2 months ago | about 1 year ago | |
Common Lisp | Common Lisp | |
GNU Affero General Public License v3.0 | MIT License |
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Petalisp
- Petalisp: Elegant High Performance Computing
- Is there a tutorial for automatic differentiation with petalisp?
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Is there a language with lisp syntax but C semantics?
While not "as fast as C" (C is not the absolute pinnacle of performance), Common Lisp is incredibly fast compared to the majority of programming languages around today. There is even a huge amount of ongoing work being done to make it faster still. We are seeing many interesting projects that make better use of the hardware in your computer (e.g. https://github.com/marcoheisig/Petalisp).
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Common Lisp Implementations in 2023
i think lisp-stat library is actually being developed. however one numerical cl library that doesnt get enough mention and is being constantly developed is petalisp for HPC
https://github.com/marcoheisig/Petalisp
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numericals - Performance of NumPy with the goodness of Common Lisp
However, if you have a lisp library that puts those semantics to use, then you could get it to employ magicl/ext-blas and cl-bmas to speed it up. (petalisp looks relevant, but I lack the background to compare it with APL.)
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New Lisp-Stat Release
> his means cl pagckages can be "done".
this is true if there is nothing functional that can be added to a package. however its very much not true for ml frameworks right now. new things are being added all the time in the field. however even in the package i linked you have the necessary ingredients for any deep learning model: cuda and back propagation. the other person mentioned convolution which i think is pretty trivial to implement but still, if you expect everything for you to be ready made then you should probably stick to tf and pytorch. if you want to explore the cutting edge and push the boundaries then i think common lisp is a good tool. as an aside it might also be interesting to note that a common lisp package (Petalisp) is being used for high performance computing by a german university
https://github.com/marcoheisig/Petalisp
- The Julia language has a number of correctness flaws
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When a young programmer who has been using C for several years is convinced that C is the best possible programming language and that people who don't prefer it just haven't use it enough, what is the best argument for Lisp vs C, given that they're already convinced in favor of C?
One trick is that Common Lisp can generate and compile code at runtime, whereas static languages typically do not have a compiler available at runtime. This lets you make your own lazy person's JIT/staged compiler, which is useful if some part of the problem is not known at compile-time. Such an approach has been used at least for array munging, type munging and regular expression munging.
mgl
- Gabor Melis - Google AI Contest Winner - Conversation and Presentation (2013) (@melisgl, author of MGL)
- MGL: A Common Lisp machine learning library
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Peter Norvig – Paradigms of AI Programming Case Studies in Common Lisp
If you are interested in machine learning, check out Gabor Melis's library: https://github.com/melisgl/mgl. It's not an area I'm super familiar with, so I can't speak to it's feature set, but I believe he used it to win a machine learning competition some years ago.
I don't think anyone's written a transformer or diffusion model with it, could be a fun challenge.
- Mgl: Common Lisp machine learning library
- what library/language combination is good for regression and classification
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New Lisp-Stat Release
although not necessarily bert or resnet the following probably has all the ingredients for what you are looking for. the author of this library is a research scientist at deepmind since 2015
https://github.com/melisgl/mgl#x-28MGL-BP-3A-40MGL-BP-20MGL-...
- Update: Μαθήματα πρόγραμματισμου.
- Why Hy?
What are some alternatives?
awesome-cl - A curated list of awesome Common Lisp frameworks, libraries and other shiny stuff.
quilc - The optimizing Quil compiler.
JWM - Cross-platform window management and OS integration library for Java
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
ghdl - Binary Manager for Github Releases
magicl - Matrix Algebra proGrams In Common Lisp.
py4cl - Call python from Common Lisp
lish - Lisp Shell
criterium - Benchmarking library for clojure
StatsBase.jl - Basic statistics for Julia