Datadobi

NGD Systems Awarded Phase II SBIR Grant From National Science Foundation

For SSD In-Situ Processing
This is a Press Release edited by StorageNewsletter.com on 2017.04.21

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NGD Systems, Inc., formerly NxGn Data and a manufacturer of SSDs for the data center, received a Small Business Innovation Research (SBIR) Phase II grant from the National Science Foundation (NSF).

This grant will support development and commercialization of NGD Systems In-Situ Processing for storage products, and is a result of a selection process. With a key goal of substantially improving overall data processing performance and energy efficiency in the data center, NGD Systems In-Situ Processing will enable the next generation computational capabilities to fuel future data analytics innovation.

"With our fundamental SSD technology currently available, we are now engaged with several datacenter customers, executing In-Situ Processing proof of concepts," said Nader Salessi, CEO and founder, NGD. "The support of the NSF through this SBIR grant allows us to further accelerate the commercialization of the product's In-Situ Processing capability, augmenting open standards and creating a seamless integration path, which is critical for the widespread adoption of computational storage."

The NSF SBIR Phase II program enables a big data paradigm shift, where processing capability is pushed as close to the data as possible. The In-Situ Processing technology extends this concept to the absolute limit by putting the computational capability into the storage itself and eliminating the need to move data to main memory prior to processing.

The technology starts with a foundation of an enterprise SSD tailored for the needs of modern data centers. Key technology added to support these capabilities include hardware-assisted QoS control, low-cost 3D-TLC and QLC NAND Flash enablement using error correction, and a proprietary elastic flash translation layer supports large capacity drives. The paradigm shift will result in the ability to perform computation directly on the data with the addition of specialized In-Situ Processing aided by hardware accelerators.

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