py4cl2
cl-cuda
py4cl2 | cl-cuda | |
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11 | 5 | |
39 | 270 | |
- | - | |
5.6 | 0.0 | |
8 days ago | almost 3 years ago | |
Common Lisp | Common Lisp | |
GNU General Public License v3.0 or later | MIT License |
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py4cl2
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An Idea for Piggybacking Python (language) ecosystem
I... recently got that working: https://github.com/digikar99/py4cl2/tree/master/cffi - Yes, CFFI! Yes, passing CL array data by reference!
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Plotting
I ended up using a fair bit of matplotlib through college and with colleagues. I too don't want to use python, but I also don't like throwing away its libraries, and I'm too lazy to invest in other* plotting ecosystems. In effect, I use up using matplotlib through py4cl/2.
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numericals - Performance of NumPy with the goodness of Common Lisp
Note that it is not my aim to replace the python ecosystem; I think that is far too lofy a goal to be of any good. My original intention was to interoperate with python through py4cl/2 or the likes, but felt that one needs a Common Lisp library for "small" operations, while "large" operations can be offloaded to python libraries through py4cl/2.
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interested in learning lisp, (specifically for games, but also for everything else including tui and gui applications for linux. currently have next to no programming knowledge, can i get forwarded some resources and some tips on what exactly i should do? any videos i should watch?
Python: Blender and Panda3D (game engine used for Disney's Toontown way back when) are both scriptable with Python. I've been able to successfully call Panda from Py4CL2 (thanks digikar for the help with that), but I have not tried with Blender yet. I think it's doable.
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Rewrite Your Scripts In LISP - with Roswell
While you are at it I may as well mention https://github.com/digikar99/py4cl2
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Good Lisp libraries for math
If performance is absolutely not a concern, then third option is using python libraries through py4cl/2. To put it differently, if calling python from lisp is not the bottleneck, then this is a feasible option.
- Using Lisp as a Dynamic Library
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What are the advantages of Hy/Hissp over python bindings for CL/Clojure?
py4cl2 (not py4cl!) author here. From the v2.9.0 docs:
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Design patterns for Lisp interop with other languages?
py4cl and py4cl2 represent a fairly pragmatic example of method 1, using an OS child process to communicate back and forth with your python code. Python is fairly popular and well-enabled with libraries, so you can delegate things to python that leverage those libraries.
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Image classification in CL? Help with starting point
If you can structure your code so that data de/serialization is not a bottleneck, then you could access the python libraries using py4cl/2.
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.
What are some alternatives?
py4cl - Call python from Common Lisp
numcl - Numpy clone in Common Lisp
criterium - Benchmarking library for clojure
farolero - Thread-safe Common Lisp style conditions and restarts for Clojure(Script) and Babashka.
numericals - CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental]
vega-lite - A concise grammar of interactive graphics, built on Vega.
Petalisp - Elegant High Performance Computing
hash-array-mapped-trie - A hash array mapped trie implementation in c.
rewrite - Automated mass refactoring of source code.