cl-cuda

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

Cl-cuda Alternatives

Similar projects and alternatives to cl-cuda

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better cl-cuda alternative or higher similarity.

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cl-cuda reviews and mentions

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 | reddit.com/r/hackerdigest | 14 Aug 2021
    A Common Lisp Library to Use Nvidia CUDA\ (0 comments)
  • A Common Lisp Library to Use Nvidia CUDA
    1 project | news.ycombinator.com | 13 Aug 2021
  • Machine Learning in Lisp
    12 projects | reddit.com/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.

Stats

Basic cl-cuda repo stats
5
255
0.0
10 months ago

takagi/cl-cuda is an open source project licensed under MIT License which is an OSI approved license.

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