added changes according to #1

README.md

@@ -1,35 +1,12 @@
 # Dask: How to execute python workloads using a Dask cluster on Vulcan
 
-Motivation: This document aims to show users how to launch a Dask cluster in our compute platforms and perform a simple workload using it.
-
-Structure:
-- [ ] [Tutorial](https://diataxis.fr/tutorials/)
-- [x] [How-to guide](https://diataxis.fr/how-to-guides/)
-- [ ] [Reference](https://diataxis.fr/reference/)
-- [ ] [Explanation](https://diataxis.fr/explanation/)
-
-To do:
-- [x] Made scripts for environment creation and deployment in the folder `local_scripts`
-- [x] Changed scripts to `deployment_scripts`
-- [x] Added step about sending python file
-
----
-
 This repository looks at a deployment of a Dask cluster on Vulcan, and executing your programs using this cluster.
 
 ## Table of Contents
-- [Prerequisites](#prerequisites)
 - [Getting Started](#getting-started)
 - [Usage](#usage)
 - [Notes](#notes)
 
-## Prerequisites
-
-Before running the application, make sure you have the following prerequisites installed in a conda environment:
-- [Conda Installation](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html): Ensure that Conda is installed on your local system. For more information on, look at the documentation for Conda on [HLRS HPC systems](https://kb.hlrs.de/platforms/index.php/How_to_move_local_conda_environments_to_the_clusters).
-- [Dask](https://dask.org/): Install Dask using conda.
-- [Conda Pack](https://conda.github.io/conda-pack/): Conda pack is used to package the Conda environment into a single tarball. This is used to transfer the environment to Vulcan. 
-
 ## Getting Started
 
 ### 1. Build and transfer the Conda environment to Hawk:
@@ -65,7 +42,7 @@ scp <your_script>.py <destination_host>:<destination_directory>
 ```bash
 qsub -I -N DaskJob -l select=1:node_type=clx-21 -l walltime=02:00:00
 ```
-Note: For multiple nodes, it is recommended to write a `.pbs` script and submit it using `qsub`.
+Note: For multiple nodes, it is recommended to write a `.pbs` script and submit it using `qsub`. Follow section [Multiple Nodes](#multiple-nodes) for more information.
 
 ### 6. Go into the directory with all code:
 
@@ -83,7 +60,8 @@ source deploy-dask.sh "$(pwd)"
 
 ## Usage
 
-To run the application interactively, execute the following command after all the cluster's nodes are up and running:
+### Single Node
+To run the application interactively on a single node, execute the following command after all the cluster's nodes are up and running:
 
 ```bash
 python
@@ -100,6 +78,35 @@ conda activate <your-env>
 ```
 Do this before using the python interpretor.
 
+### Multiple Nodes
+To run the application on multiple nodes, you need to write a `.pbs` script and submit it using `qsub`. Follow lines 1-4 from the [Getting Started](#getting-started) section. Write a `submit-dask-job.pbs` script:
+
+```bash
+#!/bin/bash
+#PBS -N dask-job
+#PBS -l select=3:node_type=rome-ai
+#PBS -l walltime=1:00:00
+
+#Go to the directory where the code is
+cd <destination_directory>
+
+#Deploy the Dask cluster
+source deploy-dask.sh "$(pwd)"
+
+#Run the python script
+python <your-script>.py
+```
+
+And then execute the following commands to submit the job:
+
+```bash
+qsub submit-dask-job.pbs
+qstat -anw # Q: Queued, R: Running, E: Ending
+ls -l # list files after the job finishes
+cat dask-job.o... # inspect the output file
+cat dask-job.e... # inspect the error file
+```
+
 ## Notes
 
 Note: Dask Cluster is set to verbose, add the following to your code while connecting to the Dask cluster:

deployment_scripts/dask-worker.sh

@@ -6,13 +6,13 @@ export DASK_SCHEDULER_HOST=$2
 
 # Path to localscratch
 echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Setting up Dask environment"
-export DASK_ENV="/localscratch/${PBS_JOBID}/dask"
+export DASK_ENV="$HOME/dask"
 mkdir -p $DASK_ENV
 
 # Extract Dask environment in localscratch
 echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Extracting Dask environment to $DASK_ENV"
-tar -xzf $CURRENT_WORKSPACE/dask-env.tar.gz -C $DASK_ENV
+#tar -xzf $CURRENT_WORKSPACE/dask-env.tar.gz -C $DASK_ENV
-chmod -R 700 $DASK_ENV
+#chmod -R 700 $DASK_ENV
 
 # Start the dask environment
 echo "[$(date '+%Y-%m-%d %H:%M:%S') - Worker $HOSTNAME] INFO: Setting up Dask environment"

deployment_scripts/deploy-dask.sh

@@ -24,7 +24,7 @@ export DASK_UI_PORT=8787
 
 echo "[$(date '+%Y-%m-%d %H:%M:%S') - Master] INFO: Starting Dask cluster with $NUM_NODES nodes."
 # Path to localscratch
-export DASK_ENV="/localscratch/${PBS_JOBID}/dask"
+export DASK_ENV="$HOME/dask"
 mkdir -p $DASK_ENV
 
 echo "[$(date '+%Y-%m-%d %H:%M:%S') - Master] INFO: Extracting Dask environment to $DASK_ENV"

deployment_scripts/deployment_scripts_reference.md

@@ -1,17 +1,5 @@
 # Reference Guide: Dask Cluster Deployment Scripts
 
-Motivation: This document aims to show users how to use additional Dask deployment scripts to streamline the deployment and management of a Dask cluster on a high-performance computing (HPC) environment.
-
-Structure:
-- [ ] [Tutorial](https://diataxis.fr/tutorials/)
-- [ ] [How-to guide](https://diataxis.fr/how-to-guides/)
-- [x] [Reference](https://diataxis.fr/reference/)
-- [ ] [Explanation](https://diataxis.fr/explanation/)
-
-To do:
-
----
-
 ## Overview
 
 This repository contains a set of bash scripts designed to streamline the deployment and management of a Dask cluster on a high-performance computing (HPC) environment. These scripts facilitate the creation of Conda environments, deployment of the environment to a remote server, and initiation of Dask clusters on distributed systems. Below is a comprehensive guide on how to use and understand each script:
@@ -34,40 +22,7 @@ Before using these scripts, ensure that the following prerequisites are met:
 
 3. **SSH Setup**: Ensure that SSH is set up and configured on your system for remote server communication.
 
-## 1. create-env.sh
+## 1. deploy-dask.sh
-
-### Overview
-
-`create-env.sh` is designed to create a Conda environment. It checks for the existence of the specified environment and either creates it or notifies the user if it already exists.
-Note: Define your Conda environment in `environment.yaml` before running this script.
-
-### Usage
-
-```bash
-./create-env.sh <conda_environment_name>
-```
-
-### Note
-
-- This script is intended to run on a local system where Conda is installed.
-
-## 2. deploy-env.sh
-
-### Overview
-
-`deploy-env.sh` is responsible for deploying the Conda environment to a remote server. If the tar.gz file already exists, it is copied; otherwise, it is created before being transferred.
-
-### Usage
-
-```bash
-./deploy-env.sh <environment_name> <destination_directory>
-```
-
-### Note
-
-- This script is intended to run on a local system.
-
-## 3. deploy-dask.sh
 
 ### Overview
 
@@ -84,7 +39,7 @@ Note: Define your Conda environment in `environment.yaml` before running this sc
 - This script is designed for an HPC environment with PBS job scheduling.
 - Modifications may be necessary for different job schedulers.
 
-## 4. dask-worker.sh
+## 2. dask-worker.sh
 
 ### Overview
 
@@ -94,9 +49,3 @@ Note: Define your Conda environment in `environment.yaml` before running this sc
 
 - Execute this script on each allocated node to connect them to the Dask scheduler.
 - Designed for use with PBS job scheduling.
-
-## Workflow
-
-1. **Create Conda Environment**: Execute `create-env.sh` to create a Conda environment locally.
-2. **Deploy Conda Environment**: Execute `deploy-env.sh` to deploy the Conda environment to a remote server.
-3. **Deploy Dask Cluster**: Execute `deploy-dask.sh` to start the Dask cluster on an HPC environment.