Teraproc R Analytics Cluster-as-a-Service

logo_r_analytics_240The Teraproc R Analytics Cluster-as-a-Service is a simple and affordable way for R users to quickly get ready-to-use R environment in the cloud. Whether you need just a single R Studio instance, or a scaled-out R supercomputer to tackle those big gnarly problems, Teraproc has a solution for you.  Pre-configured with a wealth of R tools and parallel frameworks, clusters can be deployed in minutes and can take advantage of Amazon spot instances to keep costs low. It is comprised of 100% open-source software components, and is scalable from single node environments to clusters comprised of thousands of nodes. What’s even better is that the service supports Amazon’s free service so you can deploy single-user R environments or small clusters entirely for free. The Teraproc R cluster-as-a-service incorporates extensions to R BatchJobs contributed by Teraproc to the community enabling Rmpi jobs to span multiple hosts, and co-exist with other R workloads under the control of a full featured workload management system that guarantees application SLAs. When selecting AWS GPU instances, users can accelerate R performance by leveraging GPU parallel processing capabilities. If you can use R Studio, you can use Teraproc’s Cluster-as-a-Service.

From single-user R environments to R-based super computers

You can review our Getting Started Guide here.



  • A complete R environment
  • No infrastructure required
  • Deploys in minutes
  • Free development clusters
  • Cost effective by leveraging AWS Spot Instances
  • Cloud-friendly auto-scaling
  • General-purpose GPU support for R model acceleration
  • BatchJobs enhancements to mix distributed Rmpi and serial jobs
  • Multi-user clusters

Unlike competing cloud-based R solutions that run R on single nodes with limited scalability, involve costly commercial software, or deliver only a single user environment, the Teraproc cluster-as-service is flexible supporting one or many users with the ability to dynamically grow clusters as large as needed for only as long as you need them. By using 100% source components, costs are kept as low and no Linux or cluster administration expertise is required.




R Cluster-as-a-Service Features

A complete, ready-to-run R environment for parallel workloads•Users are productive immediately
•No integration or special skills required
•Developers use R studio and are insulated from the underlying complexities of the cluster
Deployed in minutes on industry’s leading cloud platform•No infrastructure required
•Reduce costs leveraging economies of scale
•Avoid the need for in-house cluster expertise
•Production proven
Comprised of 100% open source components•Avoid restrictive license agreements and fees
•Preserve strategic flexibility
•Keep costs low
Cloud-friendly auto-scaling•Run large-scale R simulations quickly
•Pay for only the resources you need
•Avoid administrative complexity
GP GPU support•Use machine instances with general purpose GPUs to dramatically improve R algorithm performance
•Simplify programming with pre-loaded, pre-configured R libraries
Take advantage of Amazon spot pricing•Accelerate model execution by taking advantage of available low-cost resources
•Automatically grow clusters to incorporate spot instances and release them when no longer needed
•Control spending by easily configuring the maximum you are willing to spend for spot instances
Multiple R parallel integrations•Pre-configured parallel environments for R – Rmpi, BatchJobs & other standard libraries
•Teraproc BatchJobs enhancements to support distributed parallel MPI jobs
Free service for R developers•Pilot the environment with no financial risk
•Develop applications on a small scale cluster, and deploy larger clusters only when needed using the same account
Commercial support•Tap our world-class cluster management expertise
•Support from the source – leaders in the development of open source workload management
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