A new perspective on processing-in-memory architecture design

  • Authors:
  • Dong Ping Zhang;Nuwan Jayasena;Alexander Lyashevsky;Joseph Greathouse;Mitesh Meswani;Mark Nutter;Mike Ignatowski

  • Affiliations:
  • Research Group, AMD, California;Research Group, AMD, California;Research Group, AMD, California;Research Group, AMD, California;Research Group, AMD, California;Research Group, AMD, California;Research Group, AMD, California

  • Venue:
  • Proceedings of the ACM SIGPLAN Workshop on Memory Systems Performance and Correctness
  • Year:
  • 2013

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Abstract

As computation becomes increasingly limited by data movement and energy consumption, exploiting locality throughout the memory hierarchy becomes critical for maintaining the performance scaling that many have come to expect from the computing industry. Moving computation closer to main memory presents an opportunity to reduce the overheads associated with data movement. We explore the potential of using 3D die stacking to move memory-intensive computations closer to memory. This approach to processing-in-memory addresses some drawbacks of prior research on in-memory computing and appears commercially viable in the foreseeable future. We show promising early results from this approach and identify areas that are in need of research to unlock its full potential.