Years ago, people in IT shops talked a lot about server sprawl stemming from the continual deployment of servers dedicated to single applications. While in many cases these servers were woefully under-utilized, IT teams couldn’t easily share the resources with other applications that were hungry for more processing power. And then came server virtualization, which made it easy to share server capacity among multiple applications, and that helped solve the problem of server sprawl.

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Today, organizations are wrestling with a similar problem but on a larger scale. That problem is cluster sprawl, which stems from the deployment of high performance computing systems dedicated to particular compute-intensive applications used in different areas, such as those for data analytics, machine learning and engineering simulations. Many organizations now find themselves with many islands of HPC that are under-utilized and difficult to manage in a unified manner.

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