cl-cuda VS numcl

Compare cl-cuda vs numcl and see what are their differences.

cl-cuda

Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs. (by takagi)

numcl

Numpy clone in Common Lisp (by numcl)
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cl-cuda numcl
5 9
268 625
- 0.6%
0.0 0.0
over 2 years ago 5 months ago
Common Lisp Common Lisp
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

cl-cuda

Posts with mentions or reviews of cl-cuda. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-26.
  • Why Lisp? (2015)
    21 projects | news.ycombinator.com | 26 Oct 2021
    > 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
    14 projects | news.ycombinator.com | 23 Oct 2021
  • Hacker News top posts: Aug 14, 2021
    3 projects | /r/hackerdigest | 14 Aug 2021
    A Common Lisp Library to Use Nvidia CUDA\ (0 comments)
  • Machine Learning in Lisp
    12 projects | /r/lisp | 4 Jun 2021
    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.

numcl

Posts with mentions or reviews of numcl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-31.

What are some alternatives?

When comparing cl-cuda and numcl you can also consider the following projects:

criterium - Benchmarking library for clojure

numericals - CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental]

py4cl - Call python from Common Lisp

hash-array-mapped-trie - A hash array mapped trie implementation in c.

rewrite - Automated mass refactoring of source code.

LoopVectorization.jl - Macro(s) for vectorizing loops.

Petalisp - Elegant High Performance Computing

april - The APL programming language (a subset thereof) compiling to Common Lisp.

lisp-matrix - A matrix package for common lisp building on work by Mark Hoemmen, Evan Monroig, Tamas Papp and Rif.

awesome-cl - A curated list of awesome Common Lisp frameworks, libraries and other shiny stuff.

py4cl2 - Call python from Common Lisp