Google Research

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

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

Abstract

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.

Learn more about how we do research

We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work