About this Course

Learn the fundamentals of parallel computing with the GPU and the CUDA programming environment! In this class, you'll learn about parallel programming by coding a series of image processing algorithms, such as you might find in Photoshop or Instagram. You'll be able to program and run your assignments on high-end GPUs, even if you don't own one yourself.

Why It’s Important to Think Parallel

Third Pillar of Science
Learn how scientific discovery can be accelerated by combining theory and experimentation with computing to fight cancer, prevent heart attacks, and spur new advances in robotic surgery.

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Intro to Parallel Programming
Course Cost
Approx. 3 months
Skill Level
Included in Course
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Join the Path to Greatness

This free course is your first step towards a new career with the Machine Learning Engineer Nanodegree Program.

Free Course

Intro to Parallel Programming

by Nvidia

Enhance your skill set and boost your hirability through innovative, independent learning.

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Course Leads

  • David Luebke
    David Luebke


  • John Owens
    John Owens


  • Mike Roberts
    Mike Roberts


  • Cheng-Han Lee
    Cheng-Han Lee


What You Will Learn

Lesson 1: GPU Programming Model

Project 1: Greyscale Conversion (for that classy touch!)

Lesson 2: GPU Hardware and Parallel Communication

Project 2: Smart Blurring (miracle product for removing wrinkles!)

Lesson 3: Fundamental Parallel Algorithms

Project 3: HDR Tonemapping (when 1000:1 contrast is not enough!)

Lesson 4: Using Sort and Scan

Project 4: Red Eye Removal (soothing relief for bright red eyes)

Lesson 5: Optimizing GPU Programs

Project 5: Accelerating Histograms (when fast isn't fast enough)

Lesson 6: Parallel Computing Patterns

Project 6: Seamless Image Compositing (polar bear in the swimming pool)

Lesson 7: The Frontiers and Future of GPU Computing

Prerequisites and Requirements

We expect students to have a solid experience with the C programming language and basic knowledge of data structures and algorithms.

See the Technology Requirements for using Udacity.

Why Take This Course

You'll master the fundamentals of massively parallel computing by using CUDA C/C++ to program modern GPUs. You'll learn the GPU programming model and architecture, key algorithms and parallel programming patterns, and optimization techniques. Your assignments will illustrate these concepts through image processing applications, but this is a parallel computing course and what you learn will translate to any application domain. Most of all we hope you'll learn how to think in parallel.

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals
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