Difference between revisions of "OpenACC Workshop"
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== Slides == | == Slides == | ||
[[media:OpenACC_Workshop.pdf|Welcome and Introduction]] | [[media:oldenburg_openacc.pdf|Agenda]]<br> | ||
[[media:OpenACC_Workshop.pdf|Welcome and Introduction]]<br> | |||
Day 1 Morning Lecture: [[media:intro1.pdf|Introduction OpenACC I]]<br> | |||
Day 1 Afternoon Lecture: [[media:intro2.pdf|Introduction OpenACC II]]<br> | |||
Day 2 Morning Lecture: [[media:advanced.pdf|Advanced OpenACC]]<br> | |||
Day 2 Afternoon Lecture: [[media:libraries.pdf|GPU-enabled Numerical Library]]<br> | |||
== Quick Guide OpenACC == | == Quick Guide OpenACC == | ||
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More info in the [[OpenACC|OpenACC Introduction]]. | More info in the [[OpenACC|OpenACC Introduction]]. | ||
== Workshop == | |||
To copy data from the course directory: | |||
cp -r /user/gilu2568/<dir> . | |||
For profiling first get allocation: | |||
salloc -p mpcg.p --gres=gpu:1 | |||
Create a script that runs an application, e.g. sincos.sh in the sincos example | |||
#!/bin/bash | |||
module load hpc-uniol-env | |||
module load PGI | |||
module load CUDA-Toolkit | |||
./sincos $@ | |||
Start the visual profiler in the background | |||
nvvp & | |||
Find out hostname for allocation | |||
srun hostname | |||
Latest revision as of 15:31, 29 March 2017
Slides
Agenda
Welcome and Introduction
Day 1 Morning Lecture: Introduction OpenACC I
Day 1 Afternoon Lecture: Introduction OpenACC II
Day 2 Morning Lecture: Advanced OpenACC
Day 2 Afternoon Lecture: GPU-enabled Numerical Library
Quick Guide OpenACC
Modules to load:
module load PGI CUDA-Toolkit
Command to compile:
pgcc -acc -ta=tesla:cc60 -o executable code.c
Command to run:
srun -p mpcg.p --gres=gpu:1 ./executable
Alternatively use partition cfdg.p.
More info in the OpenACC Introduction.
Workshop
To copy data from the course directory:
cp -r /user/gilu2568/<dir> .
For profiling first get allocation:
salloc -p mpcg.p --gres=gpu:1
Create a script that runs an application, e.g. sincos.sh in the sincos example
#!/bin/bash module load hpc-uniol-env module load PGI module load CUDA-Toolkit ./sincos $@
Start the visual profiler in the background
nvvp &
Find out hostname for allocation
srun hostname
