When most people speak of exascale supercomputers, they tend to focus on the computational aspect of these systems
"That's certainly understandable inasmuch as exascale has been generally equated with performing calculations at the level of exaflops.
But storage for these machines comes with its own set of challenges, and they are compounded by the growing use of machine learning and the increasingly important role analytics is playing in learning in supercomputing workflows.
Last year the US Department of Energy held a workshop to identify these storage challenges and begin to devise a strategy to address them over the next five to seven years. The resulting 134-page report lays out the importance of dealing with these issues proactively and offers a roadmap of sorts on what kinds of research to pursue in order to meet these challenges..."
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