Self-driving cars, machine learning and augmented reality are some of the examples of modern applications that involve parallel computing.
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.
This Lecture is accompanied by the simpleExample.cu code. Examples are provided as .cu files instead of Visual Studio or Eclipse projects to avoid compatibility issues. Use the instructions detailed in Lecture #5 to create your own projects.
This Lecture is accompanied by the simpleExampleNonAligned.cu, simpleExampleNonConsecutive.cu and simpleExampleDouble.cu codes. Examples are provided as .cu files instead of Visual Studio or Eclipse projects to avoid compatibility issues. Use the instructions detailed in Lecture #5 to create your own projects.
This Lecture is accompanied by the adjacentDifferences.cu code. Examples are provided as .cu files instead of Visual Studio or Eclipse projects to avoid compatibility issues. Use the instructions detailed in Lecture #5 to create your own projects.
This Lecture is accompanied by the movingAverage.cu code. Examples are provided as .cu files instead of Visual Studio or Eclipse projects to avoid compatibility issues. Use the instructions detailed in Lecture #5 to create your own projects.
This Lecture is accompanied by the simpleExample2D.cu code. Examples are provided as .cu files instead of Visual Studio or Eclipse projects to avoid compatibility issues. Use the instructions detailed in Lecture #5 to create your own projects.
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