GPU Computing - WMM9AM40
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Goals
This course examines technologies that are for the use of special-purpose hardware originally designed for graphics and games to solve general-purpose computing problems. We will address the hardware aspects (architectures, memory hierarchy), software aspects (CUDA/OpenCL) and algorithms aspects (tiling, reduction, pipeline,...) The design process of a parallel application will also be discussed.
Content - Introduction to parallelism and hardware concepts
Memory organisation and core organisation
#Software libraries for programming special purpose hardware
Introduction to OpenCL and CUDA
#Memory optimisation
Multilevel memory organisation and computation placement - Control Flow
Separation of tasks between CPU and special-purpose hardware - Parallel programming patterns
Study of the of the parallel pattern - Project
PrerequisitesC/C++ Programming. Algorithms
Tests Project based assessment on a student chosen subject.
The project is done in two phases : the first one, in class with some specific requirements and the second one is exploratory. (NPR)
N1= NPR
N2 = (NPR+E)/2
NPR = Evaluation du projet
E = Examen écrit de rattrapage (écrit)
The exam is given in english only 
Calendar The course exists in the following branches:
- Curriculum - Master in Applied Mathematics - Semester 9 (this course is given in english only
) - Curriculum - Master in Computer Science - Semester 9 (this course is given in english only
)
see
the course schedule for 2022-2023
Bibliography Parallel Computing: Principles and Practice - T. J. Fountain
Patterns for Parallel Programming - Timothy G. Mattson, Beverly A. Sanders, Berna L. Massingill
Introduction to Parallel Computing - Ananth Grama, George Karypis, Vipin Kumar, Anshul Gupta
CUDA by Example: An Introduction to General-Purpose GPU Programming - Jason Sanders, Edward Kandrot
Heterogeneous Computing with OpenCL de Benedict Gaster
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Date of update September 21, 2022