specialization-store
A different type of generic function for common lisp. (by markcox80)
numericals
CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental] (by digikar99)
| specialization-store | numericals | |
|---|---|---|
| 1 | 6 | |
| 28 | 47 | |
| - | - | |
| 0.0 | 7.7 | |
| over 3 years ago | about 1 month ago | |
| Common Lisp | Common Lisp | |
| GNU General Public License v3.0 or later | 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.
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.
specialization-store
Posts with mentions or reviews of specialization-store.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-21.
-
polymorphic-functions - Possibly AOT dispatch on argument types with support for optional and keyword argument dispatch
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.
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
How about the semantics? Nevermind, I looked -- utter nonsense, just like numpy.
-
Good Lisp libraries for math
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
*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
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
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 specialization-store and numericals you can also consider the following projects:
cl-parametric-types - (BETA) C++-style templates for Common Lisp
cl-cuda - Cl-cuda is a library to use NVIDIA CUDA in Common Lisp programs.
nyxt - Nyxt - the hacker's browser.
py4cl - Call python from Common Lisp
dense-arrays - Numpy like array object for common lisp
py4cl2 - Call python from Common Lisp
Petalisp - Elegant High Performance Computing
specialized-function - Julia-like dispatch for Common Lisp
polymorphic-functions - A function type to dispatch on types instead of classes with partial support for dispatching on optional and keyword argument types.
numcl - Numpy clone in Common Lisp
extensible-compound-types - User defined compound types in Common Lisp
specialization-store vs cl-parametric-types
numericals vs cl-cuda
specialization-store vs nyxt
numericals vs py4cl
specialization-store vs dense-arrays
numericals vs py4cl2
numericals vs Petalisp
numericals vs dense-arrays
numericals vs specialized-function
numericals vs polymorphic-functions
numericals vs numcl
numericals vs extensible-compound-types