Low-power motion estimation processor with 3D stacked memory

Shuping Zhang, Jinjia Zhou, Dajiang Zhou, Shinji Kimura, Satoshi Goto

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Motion estimation (ME) is a key encoding component of almost all modern video coding standards. ME contributes significantly to video coding efficiency, but, it also consumes the most power of any component in a video encoder. In this paper, an ME processor with 3D stacked memory architecture is proposed to reduce memory and core power consumption. First, a memory die is designed and stacked with ME die. By adding face-to-face (F2F) pads and through-silicon-via (TSV) definitions, 2D electronic design automation (EDA) tools can be extended to support the proposed 3D stacking architecture. Moreover, a special memory controller is applied to control data transmission and timing between the memory die and the ME processor die. Finally, a 3D physical design is completed for the entire system. This design includes TSV/F2F placement, floor plan optimization, and power network generation. Compared to 2D technology, the number of input/output (IO) pins is reduced by 77%. After optimizing the floor plan of the processor die and memory die, the routing wire lengths are reduced by 13.4% and 50%, respectively. The stacking static random access memory contributes the most power reduction in this work. The simulation results show that the design can support real-time 720p @ 60 fps encoding at 8MHz using less than 65mW in power, which is much better compared to the state-of-the-art ME processor

Original languageEnglish
Pages (from-to)1431-1441
Number of pages11
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number7
Publication statusPublished - 2015 Jul 1


  • 3dic design
  • Low power design
  • Memory stacking
  • Motion estimation processor

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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