cleaning up demos (#313)

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos

* cleaning up demos
This commit is contained in:
William Falcon
2019-10-05 16:39:05 -04:00
committed by GitHub
parent f7d762416c
commit 07c5d22ae3
9 changed files with 194 additions and 99 deletions
+12 -2
View File
@@ -4,7 +4,17 @@ To run this demo which launches a single job that trains on 2 nodes (2 gpus per
1. Log into the jumphost node of your SLURM-managed cluster.
2. Create a conda environment with Lightning and a GPU PyTorch version.
3. Submit this script.
3. Choose a script to submit
#### DDP
Submit this job to run with distributedDataParallel (2 nodes, 2 gpus each)
```bash
sbatch job_submit.sh --env=YourEnv
sbatch ddp_job_submit.sh YourEnv
```
#### DDP2
Submit this job to run with a different implementation of distributedDataParallel.
In this version, each node acts like DataParallel but syncs across nodes like DDP.
```bash
sbatch ddp2_job_submit.sh YourEnv
```