More DATA Same Budget: How to Reduce Storage Costs for Research Computing
Data growth is relentless and inevitable, as data has come to define many aspects of research computing. Simulation data, ever more sophisticated sensor data, and now the rise of machine learning all contribute to the accelerating pace of data growth.
Much of this data will be stored forever, either as a result of researcher preference and/or data compliance requirements. The combination of persistent data growth, the desire to keep everything, and relatively flat storage budgets mandates a more intelligent, highly scalable, and preferably secure long-term data storage infrastructure. As we march closer to exascale environments becoming the norm, existing storage technologies are being pushed well beyond their initial design capabilities.
Learn how archive is different than backup, how much data should be archived, and how to architect a comprehensive HSM solution using new data management technologies that can handle this accelerating growth today and well into the future.