COMP52315_GPU_Practicals

Please tackle the tasks yourself first, before looking at the solutions :-)

Start an interactive session on a GPU on NCC:

Go to the Learn Ultra page to find out how to connect to NCC via the commandline.

Once there, execute the following to access a GPU node:

srun -c 2 --gres=gpu:1 --partition=tpg-gpu-small --pty /bin/bash

Compilation of CUDA code on NCC

module load cuda/12.0

nvcc your_source_code.cu -o your_executable

Compilation of OpenMP code with CPU and GPU support

module load nvidia-hpc

nvc++ -fopenmp -mp=gpu test.cpp -o test_executable

Environment variables to adjust the number of threads used by OpenMP

OMP_NUM_THREADS

OMP_NUM_TEAMS

OMP_THREAD_LIMIT

Pkease note that these are upper bounds and do not guarantee that the ocde is executed with this exact number of threads. For instance, slurm might overwrite these values dependent on the reservation parameters.

Compilation of SYCL code on NCC

module load llvm-clang module load cuda/11.5 clang++ -fsycl -fsycl-targets=nvptx64-cuda my_source_code.cpp -o my_executable