高性能计算中的Python编程

Python in High Performance Computing

Learn how to analyse Python programmes and identify performance barriers to help you work more efficiently.

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FutureLearn
  • 完成时间大约为 4
  • 初级
  • 英语
注:本课程由FutureLearn和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Improve performance of Python programs

Apply parallelisation techniques using Python

Calculate numerical expressions efficiently in Python

Identify performance bottlenecks in Python programs

Develop higher performance extensions to Python

课程概况

The Python programming language is popular in scientific computing because of the benefits it offers for fast code development. The performance of pure Python programs is often suboptimal, but there are ways to make them faster and more efficient.

On this course, you’ll find out how to identify performance bottlenecks, perform numerical computations efficiently, and extend Python with compiled code. You’ll learn various ways to optimise and parallelise Python programs, particularly in the context of scientific and high performance computing.

课程大纲

Performance challenges of Python programming language

Performance analysis of Python programs

Efficient numerical calculations with NumPy

Using compiled code with Python

Interfacing Python to libraries written in other programming languages

Parallel programming with Python

面向人群

The course is designed for Python programmers who want to speed up their codes. You should be familiar with the basics of the Python programming language.

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