change environment.yaml to install Ray

.gitignore

@@ -0,0 +1 @@
+__pycache__

README.md

@@ -1,36 +1,21 @@
-# Dask: How to execute python workloads using a Dask cluster on Vulcan
+# Ray: How to launch a Ray Cluster on Hawk?
 
-Wiki link: 
-
-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.
+This guide shows you how to launch a Ray cluster on HLRS' Hawk system.
 
 ## Table of Contents
-- [Prerequisites](#prerequisites)
-- [Getting Started](#getting-started)
-- [Usage](#usage)
-- [Notes](#notes)
+- [Ray: How to launch a Ray Cluster on Hawk?](#ray-how-to-launch-a-ray-cluster-on-hawk)
+  - [Table of Contents](#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:
-- [Python 3.8.18](https://www.python.org/downloads/release/python-3818/): This specific python version is used for all uses, you can select it using while creating the conda environment. 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).
-- [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.
+- [Python 3.9](https://www.python.org/downloads/release/python-3818/): This specific python version is used for all uses, you can select it using while creating the conda environment. 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).
+- [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, 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).
+- [Ray](https://dask.org/): You can install Ray inside 
 - [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
@@ -41,7 +26,7 @@ Before running the application, make sure you have the following prerequisites i
    git clone <repository_url>
    ```
 
-2. Go into the direcotry and create an environment using Conda and enirvonment.yaml. Note: Be sure to add the necessary packages in environemnt.yaml:
+2. Go into the directory and create an environment using Conda and environment.yaml. Note: Be sure to add the necessary packages in environment.yaml:
 
    ```bash
    ./deployment_scripts/create-env.sh <your-env>

deployment_scripts/deployment_scripts_reference.md

@@ -1,4 +1,4 @@
-# Reference Guide: Dask Cluster Deployment Scripts
+# Reference: Cluster Deployment Scripts
 
 Wiki link: 
 

deployment_scripts/environment.yaml

@@ -1,9 +1,21 @@
+name: ray
 channels:
   - defaults
-  - conda-forge
 dependencies:
-  - python=3.8.18
-  - dask
-  - numpy
+  - python=3.10
+  - pip:
+    - ray==2.8.0
+    - dask==2022.10.1
+    - torch
+    - pydantic<2
+    - six
+    - torch
+    - tqdm
+    - pandas<2
     - scikit-learn
-  - conda-pack
+    - matplotlib
+    - optuna
+    - seaborn
+    - tabulate
+    - jupyterlab
+    - autopep8