A parallel Cluster is an open-source tool by Amazon Web Services (AWS). It focuses on the deployment and management of higher performance computing (HPC) clusters in the cloud. AWS built this management tool in the CfnCluster, an open-source project.
You can use Parallel Cluster to create a high-performance computing environment in AWS. It helps in setting up automatic computer resources and shared filesystems. Experts recommend using this management tool with Batch and Slurm, which are batch schedulers.
Besides, Parallel Cluster enables you to build high-level workflows. For instance, you can create a genomic portal to automate the sequencing workflow of the entire DNA. In today’s article, we will discuss some essential features of the Parallel Cluster. Read on!
Parallel Cluster Features
Parallel Cluster deploys a simple text file to design, model, and provide the required resources for HPC applications. It ensures the process is automated and secured. Parallel Cluster supports a wide range of job schedulers, including Torque, SGE, AWS Batch, and Slurm. The purpose is to submit jobs easily without any errors.
Automatic Resource Scaling
Automatic Resource Scaling is an essential feature of AWS Parallel Cluster. Users can use a simple text file to design, model, and provision resources. That way, you can scale the resources dynamically for your HPC applications automatically and securely.
A Batch Scheduler
Parallel Cluster enables you to set up multiple queues and prioritize them with different levels. You can store batch jobs in the queues until you have computed resources to run the job.
It helps you assess when to run jobs, where and how to execute them based on your resource requirements for each job. Besides, Parallel Cluster sets the priority of each queue using the batch scheduler. It runs jobs in different priorities on computing resources, such as optimized CPU and memory.
Parallel Cluster by AWS allows you to provide resources in a repeatable and safer manner. It enables you to create and recreate your infrastructure without implementing manual operations or custom scripts.
Parallel Cluster allows for easy cluster management. It schedules work and manages the state of each cluster resource. For example, you need cluster management when running a MapReduce job through Apache Spark or Apache Hadoop.
Migration to the Cloud
Parallel Clusters has compatibility and support for various operating systems (OS) and batch schedulers. It enables you to migrate existing higher-performance computing workloads to the cloud with slight modifications. Sometimes, users don’t need to make modifications because the process is done automatically.
Parallel Cluster supports the CentOS-8 OS, which means you can choose it as your base operating system to run clusters on different architectures, such as X86 and ARM. It also allows you to customize and extend cluster functionalities. You can add new dashboards and extend their functionalities in the cloud.
Resources in high-performance computing clusters, such as storage, instances, schedulers, and networking, are essential assets that require thorough monitoring and analyses. It is challenging to organize and display these metrics as the infrastructure scale increases or changes or overtime. You can cope with these challenges by hiring professional cloud computing services.