Hands On Training

Python in High Performance Computing

Future Learn

4.5

(4)

Course Features

Duration

4 weeks

Delivery Method

Online

Available on

Lifetime Access

Accessibility

Mobile, Desktop

Language

English

Subtitles

English

Level

Advanced

Effort

4 hours per week

Teaching Type

Self Paced

Course Description

Because of its speed and ease of use, Python is a popular programming language in scientific computing. Although pure Python programs are often slow and inefficient, there are many ways to improve their performance.

This course will teach you how to identify performance bottlenecks and perform efficient numerical computations. You'll also learn how to extend Python with compiled codes. There are many ways to optimize and parallelise Python programs in scientific and high-performance computing.

Course Overview

Alumni Network

Human Interaction

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

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

Target Students

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

Course Content

Expand all sections

Module 1: Performance challenges of Python programming language

Module 2: Performance analysis of Python programs

Module 3: Efficient numerical calculations with NumPy

Module 4: Using compiled code with Python

Course Instructors

Martti Louhivuori

Instructor

Expert on high-performance computing working at CSC.fi

Jussi Enkovaara

Instructor

Senior application scientist at the Finnish national supercomputing center CSC - IT Center for Science.

Course Reviews

Average Rating Based on 4 reviews

4.3

50%

25%

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