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Near-Data Processing: Insights from a MICRO-46 Workshop

Rajeev Balasubramonian
Troy Manning
Jaime H. Moreno
Richard Murphy
Ravi Nair
Steven Swanson
IEEE Micro (Special Issue on Big Data), vol. 34 (2014), pp. 36-43


The cost of data movement in big-data systems motivates careful examination of near-data processing (NDP) frameworks. The concept of NDP was actively researched in the 1990s, but gained little commercial traction. After a decade-long dormancy, interest in this topic has spiked. A workshop on NDP was organized at MICRO-46 and was well attended. Given the interest, the organizers and keynote speakers have attempted to capture the key insights from the workshop into an article that can be widely disseminated. This article describes the many reasons why NDP is compelling today and identifies key upcoming challenges in realizing the potential of NDP.