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Numba: a LLVM-based Python JIT compiler
Abstract
Dynamic, interpreted languages, like Python, are attractive for domain-experts and scientists experimenting with new ideas. However, the performance of the interpreter is often a barrier when scaling to larger data sets. This paper presents a just-in-time compiler for Python that focuses in scientific and array-oriented computing. Starting with the simple syntax of Python, Numba compiles a subset of the language into efficient machine code that is comparable in performance to a traditional compiled language. In addition, we share our experience in building a JIT compiler using LLVM[1].
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Python for scientific computing
Oliphant, T. E. (2007) · Computing in Science & Engineering · doi:10.1109/mcse.2007.58 · Cited by 3,303 · cited 2×
“Numba: A LLVM-based Python JIT Compiler Siu Kwan Lam Antoine Pitrou Stanley Seibert Continuum Analytics Continuum Analytics Continuum Analytics Austin, Texas Austin, Texas Austin, Texas slam@continuum.io apitrou@continuum.io sseibert@continuum.io ABSTRACT Dynamic, interpreted languages, like Python, are attractive for…”
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Metadata
- Authors
- Lam, S. K., Pitrou, A., & Seibert, S.
- Venue
- Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC
- Publisher
- ACM
- Published
- 2015-11-15
- Pages
- 1-6
- OpenAlex
- W2245493112
- Cited by
- 1,514
- References
- 1
- FWCI
- 12.68
- Type
- conference paper
- Language
- en
- Open access
- closed
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