Low cost ECC schemes for improving the reliability of DRAM+PRAMMAIN memory systems

Manqing Mao, Chengen Yang, Zihan Xu, Yu Cao, Chaitali Chakrabarti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Hybrid memory, where the DRAM acts as a buffer to the PRAM, is a promising configuration for main memory systems. It has the advantages of fast access time, high storage density and very low standby power. However, it also has reliability issues that need to be addressed. This paper focuses on low cost Error Control Coding (ECC)-based schemes for improving the reliability of hybrid memory. We propose three candidate systems that all guarantee block failure rate of 10-8 but differ in whether the DRAM and/or PRAM data get coded and the strength of the corresponding ECC code. The candidate systems are evaluated with respect to lifetime, Instruction Per Cycle (IPC) and energy. We show that (1) at lower Data Storage Time (DST), the proposed system which has different ECC schemes for DRAM and PRAM has the longest lifetime and one of the highest IPC; (2) at higher DST, stronger ECC codes are necessary for all the systems and longer lifetime can be achieved at the cost of decrease in IPC.

Original languageEnglish (US)
Title of host publicationIEEE Workshop on Signal Processing Systems, SiPS
Subtitle of host publicationDesign and Implementation
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479965885
DOIs
StatePublished - Dec 15 2014
Event2014 IEEE Workshop on Signal Processing Systems, SiPS 2014 - Belfast, United Kingdom
Duration: Oct 20 2014Oct 22 2014

Publication series

NameIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
ISSN (Print)1520-6130

Other

Other2014 IEEE Workshop on Signal Processing Systems, SiPS 2014
CountryUnited Kingdom
CityBelfast
Period10/20/1410/22/14

Keywords

  • DRAM+PRAM
  • Hybrid main memory
  • error correction codes
  • reliability

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Applied Mathematics
  • Hardware and Architecture

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