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Dense-arrays Alternatives
Similar projects and alternatives to dense-arrays
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WorkOS
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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numericals
CFFI enabled SIMD powered simple-math numerical operations on arrays for Common Lisp [still experimental]
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polymorphic-functions
A function type to dispatch on types instead of classes with partial support for dispatching on optional and keyword argument types.
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dense-numericals
Discontinued Numerical Computing library with https://github.com/digikar99/dense-arrays as the front-end
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SaaSHub
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The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better dense-arrays alternative or higher similarity.
dense-arrays reviews and mentions
Posts with mentions or reviews of dense-arrays.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-20.
- dense-arrays: Numpy like array object for common lisp
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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.
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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.
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polymorphic-functions - Possibly AOT dispatch on argument types with support for optional and keyword argument dispatch
Currently I have put successfully this to use at dense-numericals - which I created over dense-arrays after finding CL arrays to be not that suitable, as compared to numpy or julia. Now, dense-numericals relies on passing the array pointer to C functions. However, IIUC, this runs into issues for what if the GC moves the arrays while the computation is still not done; is this worry valid? I think I ran into this while running multithreaded tests on CCL, ending up in segfaults.
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Confused about array runtime type checking in SBCL
Shameless unstable plug: I think it should be possible to provide type checking with a different backend that does not upgrade the types at https://github.com/digikar99/dense-arrays - the backend things are themselves unstable though.
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Past, Present, and Future of Lisp
In semi-production, ideally the problems are best represented using state diagrams, but I don't see a way to comfortably represent graphs in textual formats. The best I see is list of lists, which doesn't feel significantly better than the spaghetti code it currently is (for instance this and this - but these are just about one function each in a larger system, so not totally worth a DSL, unless there existed a defacto state-diagram DSL which everyone could be expected to know.
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A note from our sponsor - WorkOS
workos.com | 25 Apr 2024
Stats
Basic dense-arrays repo stats
7
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6.3
25 days ago
The primary programming language of dense-arrays is Common Lisp.
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