Cray® CS300™ Cluster Supercomputers for Hadoop®
High performance clusters supporting hybrid workloads
Cray cluster supercomputers are used to address the most demanding computing needs in the scientific community. Increasingly, organizations are also turning to frameworks like Hadoop® to process and analyze large volumes of scientific data generated by traditional HPC workloads — and combining this data with external datasets and real-time data sources such as sensor networks — to aid advanced scientific discovery.
Using Hadoop to process big data requires optimal performance across a wide range of analytic workloads, combined with the ability to scale out infrastructure to handle ever-increasing volumes and types of data. In addition, scientific computing users need to maximize shared computing resources — making the ability to schedule and run analytics workloads on demand, side by side with traditional scientific computing jobs, a key emerging need in supercomputing installations.
The Cray® CS300™ cluster supercomputer series provides the tools necessary to handle mixed workloads, enabling analytics for scientific computing. By combining job scheduling, resource management and Cray’s Advanced Cluster Engine (ACE™) system management software in a single foundation, Cray cluster supercomputers allow users to derive maximum value from Hadoop while retaining the ability to run traditional HPC workloads on the same cluster.
- Flexible. HPC and analytic workloads leverage Apache™ Hadoop® on the same cluster supercomputer.
- High Performance. Validated and optimized technologies provide performance for the most demanding hybrid workloads.
- Reliable. Reliable service levels are built on proven technologies like Cray’s ACE system management software.
- Maintainable. Systems are easy to maintain and update with entire-solution management tools and services.
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