Migrating HPC Workloads to the Cloud

High-performance computing (HPC) is a resource collection that provides state-of-the-art solutions to complex problems. Unlike personal computers, HPC services focus on delivering supercomputers that can manage HPC workloads. 

There are various reasons why HPC companies and users adopt cloud computing. Cloud hardware improves on-premises infrastructure dynamically, especially for use cases that require GPUs. 

Migrating HPC Workloads to the cloud offers various benefits, such as auto-scaling, orchestration, big data analytics, development tools, and software management. Some of the cloud’s advanced features are: 

  • Streamlined HPC data and workflows 
  • End-to-end traceability and management
  • Improve HPC workloads efficiency 

Best Cloud Options for High-Performance Computing 

Companies migrate HPC workloads to the cloud to take advantage of the pay-as-you-go computing resources. Cloud computing offers instant resource availability and large capacity, allowing you to scale your numerous applications within the cloud.

You can design instances to meet your needs and move instances to and from similar clouds. Various models exist today that you can use to utilize cloud resources for high-performance computing workloads. Read on! 

Focus on the Storage Space 

According to Clovertex, a professional and reputable cloud computing company, Amazon EBS offers advanced block storage, allowing you to store your reads temporarily. You can take advantage of Amazon EBS for your high-performance computing workloads using memory and genomics workloads. 

Using EBS, you can optimize your high IOPS, streamline instances by default on C5 and M5, reduce network contention, improve stability, and enhance your HPC application performance. 

If your HPC workloads have higher input-output requirements, you can use a parallel file system developed by AWS, enabling you to optimize your HPC. Make sure you use Amazon FSX for Lustre to improve scalability and performance. 

Automation and Orchestration 

Clovertex recommends focusing on automation and orchestration to ensure your HPC workloads run smoothly on the cloud. For instance, you can AWS HPC instances for schedulers and batch management. Likewise, AWS enables you to develop scheduling and batch management through the spot instance market or SQS and Cloud-Watch. 

However, if you want to streamline your HPC workloads or operations, you can also use the AWS batch to organize and manage your IT resources. Bear in mind that AWS provides Parallel Clusters, allowing you to run virtual HPC clusters effectively and quickly. Create Cloud Formation Templates to automate your entire HPC workloads. 

Consider Your Deployments 

According to Clovertex experienced cloud computing IT professionals, limiting deployments size is essential when planning your higher-performance computing workloads. Although there is no limit, Clovertex recommends about 1,000 cores or 500 virtual machines per deployment. 

Remember, if you exceed more than this number, you will end up losing your active instances, leading to delays in implementation and issues in IP swapping. Therefore, it is wise to hire a professional cloud computing team like Clovertex to streamline your deployments and manage your HPC workloads. 

Use the HPC Pack Client Utility

Suppose you are using Azure for your HPC workload management. In that case, we recommend using the HPC Pack Client Utility because it helps you avoid slow performance due to users’ connectivity to the root node on a remote desktop. Instead of using the remote desktop services, you can use the HPC PACK Client Utility to solve this problem. 

Final Words 

Migrating HPC Workloads to the cloud is a successful strategy for companies. However, it is not an easy task, meaning you need careful planning and preparation. On the other hand, professional cloud computing services like Clovertex can help you migrate your HPC workloads to the cloud efficiently and quickly. Contact us today