Jul 02 2019
Enhanced Edge Computing is #7 in our series on corporate data management and digital transformation tech trends. Edge computing pushes applications, data, and computing power away from centralized points to locations closer to the user to allow real-time data analytics. It is more efficient and practical- and a big step back from cloud computing. For edge computing, the primary objective is speed. Reducing latency improves user experience, and in the case of a self-driving car, may be the difference between life and death. Additionally, edge computing has the advantage of reducing security risks particularly since they do not require persistent connection to the cloud.
A challenge for edge computing application is the limited space and power available for things like self-driving cars and aircraft engine management systems. Most edge computing cases cannot rely on standard datacenter equipment. Computational storage embeds the processing capabilities within the storage devices. Our Newport Platform provides the technology for in-situ processing with hardware to accommodate AI and encryption acceleration with extremely powerful computing capability coupled with extremely low power consumption.
An Intel S72000APR SBC contains an Intel Xeon Phi 7200 processor, can hold 384GB of RAM, consumes 320W of power, and take up 338 cubic inches of space (6.8” x 14.2” x 3.5”). Throw in a 32GB SSD, and the power consumption goes up to 332W. That is almost 28 times the power consumed by the U.2 version of the Newport Computational Storage SSD. It is also 52 times the space taken up by the U.2 Newport. For an edge application such as a self-driving vehicle or an engine management system, the power and space savings provided by computational storage is substantial.
Enhanced edge computing as a tech trend? We have the expertise to address your edge computing application needs. Find out how Computational Storage can help your edge computing application save power and space, contact me.