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Management and optimization for nonvolatile memory-based hybrid scratchpad memory on multicore embedded processors

  • Oklahoma State University
  • Chongqing University
  • City University of Hong Kong
  • University of Texas at Dallas

Research output: Contribution to journalArticlepeer-review

Abstract

The recent emergence of various Non-Volatile Memories (NVMs), with many attractive characteristics such as low leakage power and high-density, provides us with a new way of addressing the memory power consumption problem. In this article, we target embedded CMPs, and propose a novel Hybrid Scratch Pad Memory (HSPM) architecture which consists of SRAM and NVM to take advantage of the ultra-low leakage power, high density of NVM, and fast access of SRAM. A novel data allocation algorithm as well as an algorithm to determine the NVM/SRAM ratio for the novel HSPM architecture are proposed. The experimental results show that the data allocation algorithm can reduce the memory access time by 33.51% and the dynamic energy consumption by 16.81% on average for the HSPM architecture when compared with a greedy algorithm. The NVM/SRAM size determination algorithm can further reduce the memory access time by 14.7% and energy consumption by 20.1% on average.

Original languageEnglish
Article number79
JournalACM Transactions on Embedded Computing Systems
Volume13
Issue number4
DOIs
StatePublished - 2015
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Data allocation
  • Energy
  • MRAM
  • Multicore processors
  • NVM
  • On-chip memory
  • PCM
  • SPM

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