AC-DIMM: associative computing with STT-MRAM

  • Authors:
  • Qing Guo;Xiaochen Guo;Ravi Patel;Engin Ipek;Eby G. Friedman

  • Affiliations:
  • University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY;University of Rochester, Rochester, NY

  • Venue:
  • Proceedings of the 40th Annual International Symposium on Computer Architecture
  • Year:
  • 2013

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Abstract

With technology scaling, on-chip power dissipation and off-chip memory bandwidth have become significant performance bottlenecks in virtually all computer systems, from mobile devices to supercomputers. An effective way of improving performance in the face of bandwidth and power limitations is to rely on associative memory systems. Recent work on a PCM-based, associative TCAM accelerator shows that associative search capability can reduce both off-chip bandwidth demand and overall system energy. Unfortunately, previously proposed resistive TCAM accelerators have limited flexibility: only a restricted (albeit important) class of applications can benefit from a TCAM accelerator, and the implementation is confined to resistive memory technologies with a high dynamic range (RHigh/RLow), such as PCM. This work proposes AC-DIMM, a flexible, high-performance associative compute engine built on a DDR3-compatible memory module. AC-DIMM addresses the limited flexibility of previous resistive TCAM accelerators by combining two powerful capabilities---associative search and processing in memory. Generality is improved by augmenting a TCAM system with a set of integrated, user programmable microcontrollers that operate directly on search results, and by architecting the system such that key-value pairs can be co-located in the same TCAM row. A new, bit-serial TCAM array is proposed, which enables the system to be implemented using STT-MRAM. AC-DIMM achieves a 4.2X speedup and a 6.5X energy reduction over a conventional RAM-based system on a set of 13 evaluated applications.