Introduction to Concurrent Programming with GPUs
This course will help prepare students for developing code that can process large amounts of data in parallel. It will focus on foundational aspects of concurrent programming, such as CPU/GPU architectures, multithreaded programming in C and Python, and an introduction to CUDA software/hardware.
Students will learn how to develop concurrent software in Python and C/C++ programming languages.
Students will gain an introductory level of understanding of GPU hardware and software architectures.
Syllabus
Syllabus - What you will learn from this course
Week 1
Course Overview
Week 2
Core Principles of Parallel Programming on CPUs and GPUs
Week 3
Introduction to Parallel Programming with C and Python
Week 4
NVidia GPU Hardware/Software
Week 5
Introduction to GPU Programming
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Can I program on my own laptop/desktop?
Yes, but you will need to update code files to the labs and assignments. For modules 4 and 5 you will need to have an Nvidia GPU installed on your machine. The in-browser environment for labs and assignments is built to allow for all required programming.
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