Commit 1990a407 authored by Ravi Tripathi's avatar Ravi Tripathi
Browse files

Modified the heading of Example 3 and removed NGC section

parent bdb07c1e
...@@ -200,11 +200,11 @@ ...@@ -200,11 +200,11 @@
singularity exec -B /data/user/$USER /data/user/$USER/rc-training-sessions/neurodebian-neurodebian-master-latest.simg dcm2nii PATH_TO_YOUR_DICOM_FILES singularity exec -B /data/user/$USER /data/user/$USER/rc-training-sessions/neurodebian-neurodebian-master-latest.simg dcm2nii PATH_TO_YOUR_DICOM_FILES
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Example 2: ## Pulling a Docker Image
In this example we are going to be pulling a singularity image from [dockerhub](https://hub.docker.com/). This singularity image contains [google-cloud-sdk tools](https://cloud.google.com/sdk/). In this example we are going to be pulling a singularity image from [dockerhub](https://hub.docker.com/). This singularity image contains [google-cloud-sdk tools](https://cloud.google.com/sdk/).
The Cloud SDK is a set of tools for Cloud Platform. It contains gcloud, gsutil, and bq command-line tools, which you can use to access Google Compute Engine, Google Cloud Storage, Google BigQuery, and other products and services from the command-line. You can run these tools interactively or in your automated scripts. The Cloud SDK is a set of tools for Cloud Platform. It contains gcloud, gsutil, and bq command-line tools, which you can use to access Google Compute Engine, Google Cloud Storage, Google BigQuery, and other products and services from the command-line. You can run these tools interactively or in your automated scripts.
...@@ -215,56 +215,25 @@ ...@@ -215,56 +215,25 @@
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
!singularity exec -B /data gcloud.simg gsutil !singularity exec -B /data/user/$USER gcloud.simg gsutil
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
To clean your directory of all the container images, you can run the command below ## Clean your directory:
%% Cell type:code id: tags:
``` python
!rm *.simg
```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Example 3: To clean your directory of all the container images, you can run the command below
[NVIDIA GPU Cloud](https://www.nvidia.com/en-us/gpu-cloud/) (NGC) offers a container registry of Docker images with over 35 HPC, HPC visualization, deep learning, and data analytics containers optimized for GPUs and delivering accelerated performance (figure 3). The registry includes some of the most popular applications including GROMACS, NAMD, ParaView, VMD, and TensorFlow.
For this example you would have to start a new Jupyter Notebook session on the 'pascalnodes' partition. Most of the settings are similar to the ones that you had in the [Git repo](https://gitlab.rc.uab.edu/rc-training-sessions/singularity_containers) for this session. you just need to add/modify the following things.
In the Environment parameter add
```
module load cuda92/toolkit/9.2.88
module load CUDA/9.2.88-GCC-7.3.0-2.30
module load Singularity/2.5.2-GCC-5.4.0-2.26
module load Anaconda3
```
And in the partition choose:
```
pascalnodes
```
You will need to create a new account on Nvidia GPU Cloud, to pull down these conatiners.
%% Cell type:code id: tags:
``` python
!singularity build vmc_gpu.simg docker://nvcr.io/hpc/vmd:cuda9-ubuntu1604-egl-1.9.4a17
```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
!singularity exec --nv vmc_gpu.simg /opt/vmd/bin/vmd -dispdev openglpbuffer -e hiv-simple-egloptix-test.vmd !rm *.simg
``` ```
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
## Building a Singularity container recipe file ## Building a Singularity container recipe file
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