Language: English | Size: 233 MB | Duration: 1h 49m
What does coalescence mean? What is Halo region? And shared memory? Learn the basics of Parallel Computing with CUDA.
What you’ll learn
Understanding the basics of parallel programming on GPU.
Understanding the basics of GPU architecture.
Writing simple programs in CUDA language.
Requirements
Experience with C/C++
Description
Self-driving cars, machine learning and augmented reality are some of the examples of modern applications that involve parallel computing.
With the availability of high performance GPUs and a language, such as CUDA, which greatly simplifies programming, everyone can have at home and easily use a supercomputer.
The aim of this course is to provide the basics of the architecture of a graphics card and allow a first approach to CUDA programming by developing simple examples with a growing degree of difficulty.
Who this course is for:
People aiming at a first approach to parallel programming on GPUs.
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