This course presents the basic of parallel programming on GPU architectures. Its main focus is on the CUDA language, but it will provide a brief overview of the main tools available on those platforms.Content
Introduction to parallel computing, GPU architectures.

    CUDA programming model: thread grid hierarchy, memory model, CUDA language, massively multi-thread architecture, execution model

    Basic GPU algorithms : sorting and reductions

    Advanced aspects: CUDA optimizations, CUDA/C++ coupling, CUDA/Python

Half of the course will be made of hands-on sessions.Learning outcomes
Understanding of the main issues in developing GPU applications. Ability to choose the most suitable tool for a given application and environment. Ability to develop a working prototype for a target application.Prerequisites
Basic knowledge of C programming in a Unix environment.

https://events.prace-ri.eu/event/64/