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Intro
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Specialized Tailored for number crunching
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Multiple targets
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Numba architecture
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Compilation pipeline
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Numba types
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Supported Python syntax Supported constructs
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Supported Python features
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Supported Python modules Standard library
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Supported Numpy features
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Limitations
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Semantic changes
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Using Numba: @vectorize
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@jit example: Ising models
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Ising model: code
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CUDA support
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CUDA example
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Installing Numba
Description:
Discover the power of Numba, a JIT compiler for fast numerical code, in this 30-minute EuroPython Conference talk by Antoine Pitrou. Gain insights into Numba's capabilities for speeding up numerical algorithms beyond fast linear algebra operations, with backends for both CPU and NVidia GPUs. Learn about Numba's use cases, expected performance levels, and inner workings. Explore the compilation pipeline, supported Python syntax and features, Numpy integration, and CUDA support. Understand Numba's architecture, limitations, and semantic changes. Follow along with practical examples, including the Ising model implementation. Suitable for Python programmers with some familiarity in scientific computing and Numpy, this talk offers valuable knowledge for those interested in high-performance Python solutions.

Numba - A JIT Compiler for Fast Numerical Code

EuroPython Conference
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