arkouda
mojo
| arkouda | mojo | |
|---|---|---|
| 1 | 20 | |
| 225 | 21,429 | |
| 0.4% | 18.8% | |
| 9.4 | 9.9 | |
| 5 days ago | 6 days ago | |
| Python | Mojo | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
arkouda
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Mojo is now available on Mac
Those interested in the intersection between Python, HPC, and data science may want to take a look at Arkouda, which is a Python package for data science at massive scales (TB of memory) at interactive rates (seconds), powered by Chapel:
* https://github.com/Bears-R-Us/arkouda
mojo
- The Mojo Programming Language
- Mojo language goes open source
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The Mojo programming language has changed its version numbering. Release v24.1.1
https://github.com/modularml/mojo/blob/main/LICENSE Is this not it?
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Dada, an Experiement by the Creators of Rust
Interesting, but the intent seems similar to Chris Lattner's new Mojo language which arguably has similar characteristics and is further along in its development.
https://docs.modular.com/mojo/
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Mojo - A New Programming Language for AI
Mojo is a programming language that combines the performance and control inherent in systems languages like C++ and Rust with the flexibility and simplicity of use typical of dynamic languages like Python. Because of its combination of performance, extensibility, and usability, its design makes it possible to construct high-performance systems, which makes it a good option for AI development.
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Mojo is now available on Mac
If you take a look at the optimized Mojo code doing the matrix multiply [1], it takes an expert to understand. It’s not just some simple for-loops in Mojo they’re comparing against.
[1] https://github.com/modularml/mojo/blob/5ce18c47a27c0c4123de1...
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Programming Languages Every Developer Should Watch Out For
Mojo truly unlocks a world of possibilities in high-performance computing.
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A Gentle Introduction to Liquid Types
For a concrete example of Liquid Haskell, see how Gabriella Gonzalez safely removed bound checks of high-performance protocol parsing, in "Scrap your Bounds Checks with Liquid Haskell" [1].
With Liquid Haskell, the bound checks are moved from runtime to compile time, semi-automatically handled by SMT-solvers. With static types, programmers can write correct programs faster, and the programs also run faster.
As an aside, speeding up programs with static analysis (constrained dynamism) are also present in Mojo (a variant of Python) or Swift [2].
[1]: https://github.com/Gabriella439/slides/blob/main/liquidhaske... "Scrap your Bounds Checks with Liquid Haskell"
[2]: https://github.com/modularml/mojo/discussions/466 "Mojo and Dynamism"
- Mojo and Dynamism
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