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@@ -92,9 +92,9 @@ jupyter lab --notebook-dir=<path-to-gpubootcamp-repo>/hpc/multi_gpu_nways/labs/
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After running Jupyter Lab, open [http://localhost:8888](http://localhost:8888/) in a web browser and start the `introduction.ipynb` notebook.
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-### Containerized Build with Singularity
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+## Optional: Containerized Build with Singularity
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-**Note:** This material is designed to primarily run in containerless environments, that is, directly on the cluster. Thus, building the Singularity container is OPTIONAL.
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+This material is designed to primarily run in containerless environments, that is, directly on the cluster. Thus, building the Singularity container is OPTIONAL.
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If containerization is desired, follow the steps outlined in the notebook [MPI in Containerized Environments](labs/CFD/English/C/jupyter_notebook/mpi/containers_and_mpi.ipynb).
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@@ -109,6 +109,12 @@ singularity run --nv multi_gpu_nways.simg jupyter lab --notebook-dir=<path-to-gp
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Then, access Jupyter Lab on [http://localhost:8888](http://localhost:8888/).
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+## Troubleshooting
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+
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+#### Compiler throws errors
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+If compiling any program throws an error related to CUDA/ NCCL/ NVHSMEM/ MPI libraries or header files being not found, ensure that `LD_LIBRARY_PATH` is correctly set. Moreover, make sure environment variables `CUDA_HOME`, `NCCL_HOME`, and `NVSHMEM_HOME` are set either during installation or manually inside each `Makefile`.
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+
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## Questions?
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Please join [OpenACC Slack Channel](https://openacclang.slack.com/messages/openaccusergroup) to raise questions.
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Anish Saxena