Book Image

High-Performance Computing with Python 3.x [Video]

By : Mohammed Kashif
Book Image

High-Performance Computing with Python 3.x [Video]

By: Mohammed Kashif

Overview of this book

Python is a versatile programming language. Many industries are now using Python for high-performance computing projects. This course will teach you how to use Python on parallel architectures. You'll learn to use the power of NumPy, SciPy, and Cython to speed up computation. Then you will get to grips with optimizing critical parts of the kernel using various tools. You will also learn how to optimize your programmer using Numba. You'll learn how to perform large-scale computations using Dask and implement distributed applications in Python; finally, you'll construct robust and responsive apps using Reactive programming. By the end, you will have gained a solid knowledge of the most common tools to get you started on HPC with Python. All code files are located on GitHub at this link https://github.com/PacktPublishing/High-Performance-Computing-with-Python-3.x
Table of Contents (8 chapters)
Chapter 5
Speeding Up Your Python Code Using Numba
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Section 3
Creating Your First Program with Numba
Once Numba has been setup correctly, we move towards implementing a basic program using Python and them optimizing it using Numba. - Implement a factorial program using Python - Explore the @jit decorator and use it to optimize code - Do a time comparison of our optimized code