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David Luebke,
John Owens,
Mike Roberts,
and
Cheng-Han Lee
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
Read more
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
Read more
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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possible dealbreakers
Explores parallel computing, a core skill for working with large datasets
In-demand skills: teaches core image processing algorithms used in photo editing apps
Taught by instructors whose backgrounds include NVIDIA
Requires familiarity with C and programming fundamentals
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Reviews summary
Solid intro to parallel programming
This course is a solid introduction to the fundamentals of parallel programming with the GPU and the CUDA programming environment. It assumes prior knowledge in C/C++ programming. While the course introduces most of the basic CUDA concepts, it places a very low emphasis on hardware/device architecture, and instead pushes coverage of this topic to the second half of the class. One downside is that less than 10% of folks who start the course finish it, so students may feel like they are on their own. However, if a student works hard, they will learn quite a bit. Overall, a good introduction to CUDA programming.
C/C++ Programming Skills Required
"It assume prior knowledge in C/C++ programming."
Code Image Processing Algorithms
"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."
Good For Learning CUDA
"Good introduction to CUDA programming."
Very Low Emphasis on Hardware/Device Architecture
"Very low emphasis on hardware/device architecture, most of it being pushed to the second half of the class."
Less Than 10% Finish
"The person I talked to said less than 10% of the folks who start the course finish it."
Hard Course
"This is a hard course."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Intro to Parallel Programming with these
activities:
Review vector operations
Show steps
Refresh your memory on basic vector operations.
Browse courses on
Vector Operations
Show steps
-
Recall vector addition and subtraction
-
Review dot and cross products
-
Practice matrix multiplication
Read 'CUDA by Example'
Show steps
Read this beginner-friendly guide to CUDA programming to enhance your understanding.
View
Cuda by Example
on Amazon
Show steps
-
Install IDE and compile CUDA code
-
Understand basic CUDA concepts
Join a study group
Show steps
Connect with peers and collaboratively tackle complex problems to enhance your understanding.
Show steps
-
Find or form a study group
-
Discuss course materials and assignments
-
Work on practice problems together
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on CUDA programming
Show steps
Supplement your learning with online resources to reinforce and expand your knowledge.
Show steps
-
Identify reputable tutorials
-
Follow step-by-step instructions
-
Practice exercises and assignments
Develop CUDA coding skills
Show steps
Try implementing basic image processing algorithms in CUDA to develop your coding skills.
Browse courses on
Parallel Programming
Show steps
-
Set up your development environment
-
Create a simple kernel function
-
Optimize your code for performance
Create a visual guide to parallel programming concepts
Show steps
Consolidate your knowledge by creating visual representations of parallel programming concepts.
Show steps
-
Choose a concept to visualize
-
Design and create your visual aid
-
Share your guide with others
Prepare a presentation on the benefits of parallel programming
Show steps
Summarize and present your understanding of the advantages of parallel programming.
Browse courses on
Parallel Programming
Show steps
-
Gather information on the topic
-
Structure and organize your presentation
-
Create visual aids to support your presentation
-
Rehearse and deliver your presentation
Build a simple image processing application using CUDA
Show steps
Apply your skills by creating a practical project that showcases your understanding of CUDA programming.
Show steps
-
Design and plan your application
-
Implement your image processing algorithm using CUDA
-
Test and debug your application
-
Deploy and share your application
Review vector operations
Show steps
Refresh your memory on basic vector operations.
Browse courses on
Vector Operations
Show steps
Show steps
Show steps
- Recall vector addition and subtraction
- Review dot and cross products
- Practice matrix multiplication
Read 'CUDA by Example'
Show steps
Read this beginner-friendly guide to CUDA programming to enhance your understanding.
View
Cuda by Example
on Amazon
Show steps
Show steps
Show steps
- Install IDE and compile CUDA code
- Understand basic CUDA concepts
Join a study group
Show steps
Connect with peers and collaboratively tackle complex problems to enhance your understanding.
Show steps
Show steps
Show steps
- Find or form a study group
- Discuss course materials and assignments
- Work on practice problems together
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on CUDA programming
Show steps
Supplement your learning with online resources to reinforce and expand your knowledge.
Show steps
Show steps
Show steps
- Identify reputable tutorials
- Follow step-by-step instructions
- Practice exercises and assignments
Develop CUDA coding skills
Show steps
Try implementing basic image processing algorithms in CUDA to develop your coding skills.
Browse courses on
Parallel Programming
Show steps
Show steps
Show steps
- Set up your development environment
- Create a simple kernel function
- Optimize your code for performance
Create a visual guide to parallel programming concepts
Show steps
Consolidate your knowledge by creating visual representations of parallel programming concepts.
Show steps
Show steps
Show steps
- Choose a concept to visualize
- Design and create your visual aid
- Share your guide with others
Prepare a presentation on the benefits of parallel programming
Show steps
Summarize and present your understanding of the advantages of parallel programming.
Browse courses on
Parallel Programming
Show steps
Show steps
Show steps
- Gather information on the topic
- Structure and organize your presentation
- Create visual aids to support your presentation
- Rehearse and deliver your presentation
Build a simple image processing application using CUDA
Show steps
Apply your skills by creating a practical project that showcases your understanding of CUDA programming.
Show steps
Show steps
Show steps
- Design and plan your application
- Implement your image processing algorithm using CUDA
- Test and debug your application
- Deploy and share your application
Career center
Learners who complete Intro to Parallel Programming will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/ps7l8h/udacity
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Intro to Parallel Programming.
Must-have for anyone who wants to learn parallel programming with CUDA. It covers everything from the basics of parallel programming to advanced techniques like thread synchronization and memory management. This book is an excellent resource for both beginners and experienced programmers.
Save
Great way to learn CUDA programming. It starts with the basics and gradually introduces more advanced topics. The book is full of examples and exercises, making it a great resource for both beginners and experienced programmers.
Save
Classic textbook on parallel computer architecture and programming. It covers everything from the basics of parallel computing to advanced topics like multithreading and GPUs. This book is an excellent resource for both students and professionals.
Save
Classic guide to design patterns. It covers everything from the basics of design patterns to advanced topics like creational, structural, and behavioral patterns. This book is an excellent resource for both students and professionals.
Classic textbook on computer architecture. It covers everything from the basics of computer organization to advanced topics like superscalar processors and memory hierarchies. This book is an excellent resource for both students and professionals.
Classic guide to preparing for technical interviews. It covers everything from data structures and algorithms to behavioral questions. This book is an excellent resource for both students and professionals.
Great guide to becoming a better programmer. It covers everything from the basics of software development to advanced topics like design patterns and refactoring. This book is an excellent resource for both students and professionals.
Save
Great guide to writing clean code. It covers everything from the basics of code formatting to advanced topics like design patterns and refactoring. This book is an excellent resource for both students and professionals.
Classic textbook on operating systems. It covers everything from the basics of operating system design to advanced topics like virtualization and cloud computing. This book is an excellent resource for both students and professionals.
Save
Collection of essays on programming. It covers everything from basic programming principles to advanced topics like code optimization and debugging. This book is an excellent resource for both experienced programmers and those just getting started.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ps7l8h/udacity
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Instructors
David Luebke
John Owens
Mike Roberts
Cheng-Han Lee
Good to know
Explores parallel computing, a core skill for working with large datasets
In-demand skills: teaches core image processing algorithms used in photo editing apps
Taught by instructors whose backgrounds include NVIDIA
Requires familiarity with C and programming fundamentals
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