4 merge requests!368Update prace.md to document the change from qprace to qprod as the default...,!367Update prace.md to document the change from qprace to qprod as the default...,!366Update prace.md to document the change from qprace to qprod as the default...,!323extended-acls-storage-section
To run a job, computational resources of DGX-2 must be allocated.
The DGX-2 is using independent PBS scheduler. Load the DGX-2 module to access the scheduler
The DGX-2 is using independent PBS scheduler. Load the DGX-2 module to access the scheduler:
```console
$ml DGX-2
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## Job Submission and Execution
The `qsub` submits the job into the queue. The command creates a request to the PBS Job manager for allocation of specified resources. The resources will be allocated when available, subject to allocation policies and constraints. After the resources are allocated the jobscript or interactive shell is executed on the allocated node.
The `qsub` submits the job into the queue. The command creates a request to the PBS Job manager for allocation of specified resources. The resources will be allocated when available, subject to allocation policies and constraints. After the resources are allocated, the jobscript or interactive shell is executed on the allocated node.
### Job Submission
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1. a Jobscript or interactive switch
!!! info
You can access the DGX PBS scheduler by loadnig the "DGX-2" module.
You can access the DGX PBS scheduler by loading the "DGX-2" module.
Submit the job using the `qsub` command:
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@@ -109,17 +109,17 @@ PBS 13.1.1 for cluster Salomon
```
!!! tip
Submit the intreractive job using the `qsub -I ...` command.
Submit the interactive job using the `qsub -I ...` command.
### Job Execution
The DGX-2 machine runs only a bare-bone, minimal operating system. Users are expected to run
**[singularity][1]** containers in order to enrich the environment accordint to the needs.
**[singularity][1]** containers in order to enrich the environment according to the needs.
Containers (Docker images) optimized for DGX-2 may be downloaded from
[NVidia Gpu Cloud][2]. Select the code of interest and
[NVIDIA Gpu Cloud][2]. Select the code of interest and
copy the docker nvcr.io link from the Pull Command section. This link may be directly used
to download the container via singularity, see example below:
to download the container via singularity, see the example below:
#### Example - Singularity Run Tensorflow
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**GPU stat**
The GPU load can be determined by `gpustat` utility.
The GPU load can be determined by the `gpustat` utility.