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Large-scale data analytics, machine learning, and big data applications often require the storage of a massive amount of data. For cost-effective high bandwidth, many data centers have used tiered storage with warmer tiers made of flashes or persistent memory modules and cooler tiers provisioned wi…
Los Alamos is working to revolutionize how scientific data management is done, moving from large Petabyte sized files generated periodically by extreme scale simulations to a record and column based approach. Along the journey, the NVMe Computational Storage efforts became a strategic way to help a…
Synthetic DNA-based data storage is a major attraction due to the possibility of storage over long periods. This technology is a solution for the current data centers, reducing energy consumption and physical storage space. Nowadays, the quantity of data generated has been growing exponentially, wh…
Data persistence on CXL is an essential enabler toward the goal of instant-on processing. DRAM class performance combined with non-volatility on CXL enables a new class of computing architectures that can exploit these features and solve real-world bottlenecks for system performance, data reliabili…
Computational Storage is a new field that is addressing performance and scaling issues for compute with traditional server architectures. This is an active area of innovation in the industry where multiple device and solution providers are collaborating in defining this architecture while actively …
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