made docker-compose descr. more compact
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README.md
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README.md
@ -12,6 +12,7 @@ toolstack on top of it to enable GPU calculations in the Jupyter notebooks.
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1. [Requirements](#requirements)
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1. [Requirements](#requirements)
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2. [Quickstart](#quickstart)
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2. [Quickstart](#quickstart)
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2. [Tracing](#tracing)
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3. [Deployment](#deployment-in-the-docker-swarm)
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3. [Deployment](#deployment-in-the-docker-swarm)
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4. [Configuration](#configuration)
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4. [Configuration](#configuration)
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@ -43,19 +44,19 @@ docker-compose (internally):
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docker run -d -p [port]:8888 gpu-jupyter
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docker run -d -p [port]:8888 gpu-jupyter
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```
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```
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Alternatively, you can configure the environment in `docker-compose.yml` and run this to deploy
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Alternatively, you can configure the environment in `docker-compose.yml` and run
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the `GPU-Jupyter` via docker-compose (under-the-hood):
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this to deploy the `GPU-Jupyter` via docker-compose (under-the-hood):
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```bash
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```bash
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./generate_Dockerfile.sh
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./generate_Dockerfile.sh
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./start-local.sh
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./start-local.sh -p 8888 # where -p stands for the port of the service
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```
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```
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Both options will run *GPU-Jupyter* by default on [localhost:8888](http://localhost:8888) with the default
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**Both options will run *GPU-Jupyter* by default on [localhost:8888](http://localhost:8888) with the default
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password `asdf`. The general usage of the `docker-compose` variant is:
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password `asdf`**.
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```bash
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./start-local.sh -p [port] # port must be an integer with 4 or more digits.
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```
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## Tracing
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With these commands we can see if everything worked well:
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With these commands we can see if everything worked well:
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```bash
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```bash
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