Parallel Cluster is a management tool used by companies to deploy and manage HPC clusters on AWS. It provides essential resources required by companies to automate and secure their HPC applications.
Parallel Clusters supports different functions, such as multiple instance types, job queues, and schedulers, including Slurm and AWS Batch. It is an open-source platform build on the CfnCluster project and released through PyPI. GitHub employs the Amazon Web Services (AWS) repository to host the source code of Parallel Cluster. Read on!
Features of Parallel Cluster
Although there are many AWS Parallel Cluster features, we will present some of the main features required for high-performance computing. The following features allow companies to simplify their processes as well as create and manage HPC clusters on AWS.
AWS Batch Support
Parallel Cluster allows companies to use AWS Batch as a job scheduler. You can use Parallel Cluster to submit distributed jobs through the AWS cluster to the Batch. AWS Batch is an important feature that allows companies, engineers, scientists, and developers to run multiple jobs on AWS.
For instance, you can run hundreds of thousands of computing jobs on AWS. Besides, it allows you to schedule multi-node parallel jobs. That way, you can run single jobs effectively, especially those with multiple EC2 instances.
EFS stands for Elastic File System. One of Parallel Cluster’s newest features is integrating EFS that supports native EFS configuration to improve storage and file management. That way, you can create and mount EFS directly on the Cluster without needing a script for post-installation.
RAID Array Support
Companies that use Parallel Cluster can create a RAID-0 or RAID-1 arrays, which can be used with their HPC cluster. RAID-0 allows you to combine multiple drives into a single one to speed up the I/O performance. Likewise, RAID-1 offers better fault tolerance by combining multiple drives into a single one. You can create RAID arrays from up to 5 EBS volumes.
Multiple EBS volumes
“Multiple EBS volumes” is one of the key features of AWS Parallel Cluster. Companies can now use EBS volumes for data storage that requires updates. For example, you can use it for the storage of database applications.
Similarly, you can use EBS volumes for throughput-intensive applications, which perform disc scans continuously. You can attach them to a single instance, but the instance and volume must exist in the same Availability Zone.
You can likewise use Multi-Attach to mount a volume to multi-instances simultaneously and accurately. However, this depends on the types of instances and volumes being used. Other features of Parallel Cluster are:
· AWS Batch integration
· Better scaling performance
· Auto-scaling all at once
· Private Cluster using proxy
· Support for Custom AMI
Benefits of Parallel Cluster
Parallel Cluster offers a wide range of benefits to hide the underlying platform’s complexities and processes. A batch scheduler, automatic resource scaling, easy cluster management, building or re-building of infrastructure automatically or without manual actions, and migration to the cloud with multiple operating system support are some of the key benefits of Parallel Cluster.
All these features or capabilities can help you streamline HPC processes for you. Resources in the HPC cluster like instances, schedulers, storage, and networking are useful assets for monitoring operations, particularly when you pay for the features you use. Another benefit of AWS Parallel Cluster is price-performance optimization and visualization or monitoring components of costs needed for their workloads.
Although Parallel Cluster is an important component of high-performance computing in the cloud and offers many benefits, some companies find it challenging to get the most out of it. If you are having trouble with Parallel Cluster, you can seek help from experienced IT professionals to streamline your HPC processes. Clovertex is a reputable company with many years of experience in HPC, and we can help you optimize your business operations.