Johns Hopkins University (via Coursera)
This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. Also, students will walk through application of GPUs to sorting of data and processing images, implementing their own software using these techniques and libraries.
By the end of the course, you will be able to do the following:
To be successful in this course, you should have an understanding of parallel programming and experience programming in C/C++.
This course will be extremely applicable to software developers and data scientists working in the fields of high performance computing, data processing, and machine learning.
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Free to audit, certificate paid