What are some advanced features of Numba that can help optimize my code?
Numba offers several advanced features like parallel execution, GPU support, and custom data types to enhance performance.
Can you explain how to use Numba for GPU acceleration?
Certainly! You can use the @cuda.jit
decorator to compile functions for execution on the GPU. Just ensure your data is on the GPU.
What about using Numba with NumPy arrays?
Numba works seamlessly with NumPy arrays, allowing you to write fast functions that operate on them without needing to change your code much.
Are there any limitations I should be aware of when using Numba?
Yes, Numba has some limitations, such as not supporting all Python features and certain data types. It's best for numerical computations.
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