Python 3.14 Will be Faster than C++ (Not really)

[Jim__]

10. Python-based compiler achieves orders-of-magnitude speedups

Codon - write Python code and then its gets compiled by a Codon compiler.

From TechXplore:

Codon is a Python-based compiler that aims to democratize high-performance computing. Credit: Alex Shipps/MIT CSAIL via Midjourney
__________________________________________________________________________________________________

...

The high-level language has earned its popularity, too, with legions of users flocking daily to the language for its ease of use due in part to its simple and easy-to-learn syntax. This led researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and elsewhere to make a tool to help run Python code more efficiently and effectively while allowing for customization and adaptation to different needs and contexts. The compiler, which is a software tool that translates source code into machine code that can be executed by a computer's processor, lets developers create new domain-specific languages (DSLs) within Python—which is typically orders of magnitude slower than languages like C or C++—while still getting the performance benefits of those other languages.

DSLs are specialized languages tailored to specific tasks that can be much easier to work with than general-purpose programming languages. However, creating a new DSL from scratch can be a bit of a headache.

"We realized that people don't necessarily want to learn a new language, or a new tool, especially those who are nontechnical. So we thought, let's take Python syntax, semantics, and libraries and incorporate them into a new system built from the ground up," says Ariya Shajii, Ph.D. , lead author on a new paper about the team's new system, Codon. "The user simply writes Python like they're used to, without having to worry about data types or performance, which we handle automatically—and the result is that their code runs 10 to 100 times faster than regular Python. Codon is already being used commercially in fields like quantitative finance, bioinformatics, and deep learning."

The team put Codon through some rigorous testing, and it punched above its weight. Specifically, they took roughly 10 commonly used genomics applications written in Python and compiled them using Codon, and achieved five to 10 times speedups over the original hand-optimized implementations. Besides genomics, they explored applications in quantitative finance, which also handles big datasets and uses Python heavily. The Codon platform also has a parallel backend that lets users write Python code that can be explicitly compiled for GPUs or multiple cores, tasks that have traditionally required low-level programming expertise.

more ...