cl-cuda VS numericals

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

cl-cuda

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

numericals

CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental] (by digikar99)
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cl-cuda numericals
5 6
268 46
- -
0.0 7.7
over 2 years ago 2 months ago
Common Lisp Common Lisp
MIT License MIT License
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.

numericals

Posts with mentions or reviews of numericals. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-02.
  • numericals - Performance of NumPy with the goodness of Common Lisp
    8 projects | /r/lisp | 2 Aug 2022
    How about the semantics? Nevermind, I looked -- utter nonsense, just like numpy.
    8 projects | /r/lisp | 2 Aug 2022
    Since the past year or two, I have been working on numericals that aims to provide the speed of NumPy with the goodness of Common Lisp. In particular, this includes the use of dynamic variables, restarts, and compiler-notes wherever appropriate. It uses CLTL2 API (and may be slightly more) under the hood to provide AOT dispatch, but nothing stops you from combining it with JAOT dispatch provided by numcl/specialized-function. This also spawned a number of projects most notably polymorphic-functions to dispatch on types instead of classes and extensible-compound-types that allows one to define user defined compound types (beyond just the type-aliases enabled by deftype. Fortunately enough, interoperation between magicl, numcl and numericals/dense-numericals actually looks plausible!
  • Good Lisp libraries for math
    7 projects | /r/lisp | 21 May 2022
    Then there is a question - do you actually need these libraries? You can optimize code in Common Lisp (type declarations, usage of appropriate data structures, SIMD instructions etc). See this: https://github.com/digikar99/numericals/tree/master/sbcl-numericals <- SIMD instructions used from SBCL (on x86; these are processor-family specific so Apple M1 will have different ones).
  • Image classification in CL? Help with starting point
    8 projects | /r/Common_Lisp | 20 Sep 2021
    *I have not; I have a couple of WIP/alpha-stage libraries like dense-arrays and numericals that could be useful; once I find the time, I want to think about if these or its dependencies can be integrated into the existing libraries including antik mentioned by awesome-cl.
  • 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.
  • polymorphic-functions - Possibly AOT dispatch on argument types with support for optional and keyword argument dispatch
    9 projects | /r/lisp | 21 May 2021
    I made this while running into code modularity issues with the numericals project I attempted last year; I did discover specialization-store, but found its goals in conflict with what I wanted to achieve; so I ended up investing in this.

What are some alternatives?

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

numcl - Numpy clone in Common Lisp

criterium - Benchmarking library for clojure

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

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

py4cl2 - Call python from Common Lisp

mgl - Common Lisp machine learning library.

clojure - The Clojure programming language

racket - The Racket repository