January 27, 2020

Accessing (HPC) High Performance Computing

By Gilad David Maayan

HPC in the Cloud Big data and Machine Learning (ML) can provide businesses with incredible insights and an innovative edge. However, to properly analyze the data collected or to train your ML models, you need access to significant computing power. While many organizations would love to use supercomputers to perform these tasks, the hefty price […]

HPC in the Cloud

Big data and Machine Learning (ML) can provide businesses with incredible insights and an innovative edge. However, to properly analyze the data collected or to train your ML models, you need access to significant computing power. While many organizations would love to use supercomputers to perform these tasks, the hefty price of these systems limits accessibility.

High Performance Computing (HPC) isn’t completely out of reach, however, even for small businesses. HPC in the cloud can provide access to substantial computing resources at an affordable cost. In this article, you’ll learn what HPC is and how you can use it in the cloud. You’ll also read an overview of HPC services currently available from cloud Service Providers.

High Performance Computing

What Is HPC?

HPC is computing performed using clusters of computers or devices that work in parallel. In HPC, many Central Processing Units (CPUs) and Graphics Processing Units (GPUs) are aggregated together to run large computational processes. Parallel processing enables you to perform complex analyses and process large amounts of data in a way that is not possible with traditional computer resources.

Benefits of HPC include:

  • Fast results—you can process large data sets and run more complicated processes in significantly less time. Parallel processes can enable you to process data in real-time.
  • Efficient resource use—You can distribute workloads across available resources for maximum resource use. This enables you to either run multiple processes at once or one large process with resource use near 100% capacity.
  • Batch processing—you can run high volume workloads with easy scheduling and minimal wait time. HPC facilitates big data analyses and complex training processes required for Machine Learning and deep learning.

Common use cases for HPC include:

  • Research and development
  • Media and entertainment editing or streaming
  • Oil and gas resource optimization and localization
  • Financial analyses and fraud detection

How Can You Use HPC in the Cloud?

HPC deployments in the cloud enable you to adapt infrastructure to your needs. You can scale resources according to workload demands without concern for how those workloads will affect other processes. You can also take advantage of service integrations to easily move data and results between HPC and standard cloud services.

Running HPC in the cloud typically requires a combination of:

  • Batch scheduling features for high-volume data sets
  • Storage services with low latency and high throughput to prevent bottlenecks
  • Userspace communication support for direct memory access
  • Bare-metal servers which support existing HPC software and tooling
  • Clustered instances or virtual machines capable of parallel processing
  • High-speed interconnects, such as Infiniband or Remote Direct Memory Access (RDMA)

In addition to the standard benefits of HPC, HPC in the cloud can provide access to cost savings and increased availability.

Cost Savings

Cloud-based HPC can reduce your overall costs and help you avoid the technical debt created by in-house systems. Pay-per-use services and access to low-priority resources can enable you to run time-insensitive HPC workloads at significant savings. Additionally, the elimination of up-front infrastructure investment makes occasional use of HPC resources feasible.

Availability and Flexibility

Cloud services support containerized workloads which enable you to automate the distribution of services and processes. Containers enable you to more easily transfer workloads and data between systems and provide protection from vendor lock-in.

Container orchestration platforms can also provide self-healing features to ensure availability. This self-healing combines with cloud-standard regional distribution of data centers and built-in redundancy to ensure high-availability.

HPC Cloud Services

All three major cloud vendors provide services and support for using HPC in the cloud. There are also a number of smaller services that offer specialized HPC services and resources. You can find an overview of the different services in the table below.

Provider Type of Service Features
Amazon Web Services Infrastructure as a Service (IaaS)

 

Public cloud only

Based on bare-metal or virtualized servers with optimized resources.

 

Operated through AWS ParallelCluster, which enables you to manage clusters.

 

You build your own deployment.

Google Cloud Platform IaaS

 

Public cloud only

Based on bare-metal or virtualized servers with optimized resources.

 

Offers a pay-per-minute option for cost efficiency.

 

You can choose to base your system on Hadoop or Google Cloud Dataflow, a batch processing system.

Azure Software as a Service (SaaS) or Platform as a Service (PaaS)

 

Hybrid or public cloud

Based on bare-metal or virtualized servers with optimized resources.

 

You can build your own or use fully-managed deployments.

 

Add-on services enable you to integrate hybrid systems with cloud HPC.

IBM Cloud SaaS or IaaS

 

Public, private, or hybrid cloud

Based on bare-metal or virtual servers with purpose-built resources.

 

Offers an HPC as a Service option via Rescale.

Sabalcore PaaS

 

Public or private cloud

Based on bare-metal, servers with purpose-built resources.

 

Offers HPC on demand or as dedicated resources.

 

They provide a fully-managed environment.

Oracle Cloud IaaS

 

Private or hybrid cloud

Based on bare-metal instances with optimized storage and networking.

 

You build your own deployment.

Penguin On Demand (POD) PaaS

 

Public, private, or hybrid cloud

Based on bare-metal servers with purpose-built resources.

 

They also offer remote management of on-premise deployments.

Conclusion

The availability of HPC in the cloud can provide you with opportunities for data utilization that were previously unavailable or impractical. With on-demand services and pay-per-use options, businesses of any size can take advantage of these aggregated resources. The ability to process and analyze data on a scale that was previously un-achievable can significantly improve your competitive advantage and innovative power.

Hopefully, this article helped you understand what HPC is and how you can access it in the cloud. If you’re interested in getting more from your data analyses or just improving the performance of your workloads, consider demoing some of the services introduced here.

By Gilad David Maayan

Gilad David Maayan

Gilad David Maayan is a technology writer who has worked with over 150 technology companies including SAP, Imperva, Samsung NEXT, NetApp and Check Point, producing technical and thought leadership content that elucidates technical solutions for developers and IT leadership. Today he heads Agile SEO, the leading marketing agency in the technology industry.
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