omarothmann / Mosaic-Montage-Workflow-With-HTCondor

Running the m101 Mosaic Montage Workflow using Linear DAG & Parallelized DAG on AWS EC2. The output will be two mosaics of m101 and their corresponding area images

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M101 Mosaic Montage Workflow with HTCondor

For this project, a HTCondor cluster consisting of 3 virtual machines running on Amazon Linux 2 AMI (HVM) - Kernel 5.10 that was setup on Amazon Web Service’s Elastic Computing Cloud (EC2) servers. The three virtual machines master, scheduler and worker was set up and paired with Network File System (NFS) before executing the workflow. The master and the scheduler shares a NFS server-client relationship respectively.

This setup was created to run a Montage m101 Mosaic workflow where the output will be two mosaics of m101 and their corresponding area images. A linear DAGMan workflow and a parallelized DAGMan workflow were created and executed to measure the performance and efficiency of the workflows to see which one is better.

💡 Running the program

To run the Linear DAG Workflow, type the following command:

$ condor_submit_dag run.dag

To run the Parallelized DAG Workflow, type the following command:

$ condor_submit_dag runparallel.dag

To check the status and progress of the job submisson, type the following command:

$ ls
$ condor_q
$ condor_q -nobatch

🎥 Demonstration Video

Demo

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Running the m101 Mosaic Montage Workflow using Linear DAG & Parallelized DAG on AWS EC2. The output will be two mosaics of m101 and their corresponding area images