This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/29058 in citations.
PRACE Training Course: Directive-based GPU programming with OpenACC
PRACE Training Course: Directive-based GPU programming with OpenACC
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to the GPU. This PRACE Training Course hosted at JSC will cover basic aspects of GPU architectures and progr...
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Personal Name(s): | Herten, Andreas (Corresponding author) |
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Hater, Thorsten / Haghighi Mood, Kaveh / Hrywniak, Markus / Kraus, Jiri | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Imprint: |
2021
|
Conference: | online 2021-10-27 - 2021-10-29 |
Document Type: |
Lecture |
Research Program: |
Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups Supercomputing & Big Data Facilities |
Link: |
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Publikationsportal JuSER |
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to the GPU. This PRACE Training Course hosted at JSC will cover basic aspects of GPU architectures and programming. Focus is on the usage of the directive-based OpenACC programming model which allows for portable application development. Examples of increasing complexity will be used to demonstrate optimization and tuning of scientific applications.Topics covered will include: Introduction to GPU/Parallel computing; Programming model OpenACC; Interoperability of OpenACC with GPU libraries (like cuBLAS and cuFFT) and CUDA; Multi-GPU Programming with MPI and OpenACC; Tools for debugging and profiling; Performance optimizationThe course consists of lectures and interactive hands-on sessions in C or Fortran. |