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Numba is an open-source JIT compiler that translates a subset of Python and NumPy into fast machine code using LLVM, via the llvmlite Python package. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.
GPU support, Overview & Alternative approaches
Explore the main themes, entities and connections around Numba. Start with the topic map, then use the sections below for research and deeper semantic analysis.
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Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
python code fast github support nvidia amd project community numpy since gpu alternative approaches release stable computing website pydata org
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Numba | Developer | Community project | 1.00 | infobox |
| Numba | License | BSD 2-clause | 1.00 | infobox |
| Numba | Operating system | Cross-platform | 1.00 | infobox |
| Numba | Original author | Continuum Analytics | 1.00 | infobox |
| Numba | Platform | x86-64, ARM64, POWER | 1.00 | infobox |
| Numba | Release | 15 August 2012; 14 years ago (2012-08-15) | 1.00 | infobox |
| Numba | Repository | github.com/numba/numba | 1.00 | infobox |
| Numba | Stable release | 0.67.0 / 12 August 2026; 12 days ago (12 August 2026) | 1.00 | infobox |
| Numba | Type | Technical computing | 1.00 | infobox |
| Numba | Website | numba.pydata.org | 1.00 | infobox |
| Numba | Written in | Python, C | 1.00 | infobox |
| Numba | is a | open-source JIT compiler that translates a subset of Python and NumPy into fast machine code using LLVM | 0.90 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.