Let’s compare AWS ParallelCluster VS AWS Batch in this article. Bobcares, as a part of our AWS Support Services offers solutions to every query that comes our way.

AWS ParallelCluster VS AWS Batch

The AWS services, ParallelCluster and Batch allow users to manage and run high-performance computing workloads. Let’s look into a detailed note on both the services in this article.

AWS ParallelCluster

1. The main function of this service is to deploy and manage HPC clusters on the AWS cloud. With this service, setting up and scaling HPC clusters becomes very simple.

2. Users have extensive control and flexibility over the cluster setup. They can specify cluster parameters, select instance kinds, alter software stacks, and set networking and storage options.

3. Although it lacks a built-in job scheduler, job scheduling tools like Slurm, Torque, or AWS Batch use this service in order to manage workload.

AWS Batch

1. Running batch computing tasks is now easy with Batch. It also runs jobs and tasks on a schedule or in reaction to particular triggers.

2. We can also abstract many of the cluster management’s issues via Batch. Users do not need to provision or set up computational resources. Instead, they submit workloads, and AWS Batch handles resource scalability and scheduling as necessary.

3. Due to the built-in job scheduler in AWS Batch, batch jobs may be submitted, managed, and prioritized more easily. Job dependencies and job retries are also supported.

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Conclusion

Depending on the particular demands and workload requirements, we can select between AWS ParallelCluster and AWS Batch. This article compares both services and points out the differences.