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Why the future of AI storage may have to exclude flash


Scale-out AI storage

A scale-out storage architecture solves the capacity challenges created Given that most AI workloads will demand dozens, if not hundreds of petaIn some cases, given the size of the workload’s data set, an organization may be better off building a large, high node count and hard disk-only cluster. That’s because these workloads are so large they completely overrun any cache tier. Also, tiering data adds overhead to the storage software, slowing it down. A high-node count, hard disk-only storage cluster may provide enough parallel performance to continue to deliver data to GPUs at speeds it can process.


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