Endurance-Aware Allocation of Data Variables on NVM-Based Scratchpad Memory in Real-Time Embedded Systems

Zhu Wang, Zonghua Gu, Min Yao, Zili Shao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)


Nonvolatile memory (NVM) has many benefits compared to the traditional static RAM, such as improved reliability and reduced power consumption, but it has long write latency and limited write endurance. Scratchpad memory (SPM) is software-managed small on-chip memory for improving system performance and predicability. We consider SPM based on spin-transfer torque RAM, a type of NVM with high performance and good endurance. We present algorithms for allocating data variables to SPM and distribute write activity evenly in the SPM address space, in order to achieve wear-leveling and prolong the lifetime of NVM. We present two optimization algorithms for minimizing system CPU utilization subject to NVM lifetime constraints: 1) an optimal algorithm based on ILP and 2) an efficient heuristic algorithm that can obtain close-to-optimal solutions.
Original languageEnglish
Article number7086044
Pages (from-to)1600-1612
Number of pages13
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number10
Publication statusPublished - 1 Oct 2015


  • non-volatile memory
  • real-time embedded
  • Scratchpad memory

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


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