Exploiting Refresh Effect of DRAM Read Operations: A Practical Approach to Low-Power Refresh

Young Ho Gong, Sung Woo Chung

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


Dynamic random access memory (DRAM) requires periodic refresh operations to retain its data. In practice, DRAM retention times are normally distributed from 64 ms to several seconds. However, the conventional refresh method uses 64 ms as the refresh interval, since it applies the same refresh interval to all DRAM rows. Thus, the conventional refresh method results in unnecessary refresh operations (eventually, energy waste) to the DRAM rows whose retention times are longer than 64 ms. In this paper, we propose a practical refresh scheme that exploits refresh effect of DRAM read operations to reduce refresh overhead. Our proposed scheme applies a refresh interval longer than the conventional refresh interval (64 ms) to the DRAM chip. In this case, weak DRAM rows (DRAM rows whose retention times are shorter than the refresh interval of the DRAM chip) cannot retain their data. In order to retain the data stored in the weak DRAM rows, the memory controller issues read operations to the weak DRAM rows every required refresh interval for the weak DRAM rows. Our evaluation results show that our proposed scheme with 192 ms refresh interval reduces average refresh energy consumption up to 66.0 percent, which in turn reduces average DRAM energy consumption up to 31.8 percent, compared to the conventional refresh method (64 ms). Our proposed scheme requires no modification to internal DRAM chip structures, but it only adds a small weak row buffer (the buffer for the weak row information) to the memory controller, which has a negligible area overhead.

Original languageEnglish
Article number7130609
Pages (from-to)1507-1517
Number of pages11
JournalIEEE Transactions on Computers
Issue number5
Publication statusPublished - 2016 May 1


  • DRAM Refresh
  • Low-power Scheme
  • Main Memory
  • Refresh Interval

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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