LL-PCM: Low-latency phase change memory architecture

Nam Sung Kim, Choungki Song, Woo Young Cho, Jian Huang, Myoungsoo Jung

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


PCM is a promising non-volatile memory technology, as it can offer a unique trade-off between density and latency compared with DRAM and flash memory. Albeit PCM is much faster than flash memory, it is still notably slower than DRAM, which can significantly degrade system performance. In this paper, we analyze a PCM implementation in depth, and identify the primary cause of PCM's long latency, i.e., a long interconnect (high resistance/capacitance) path between a cell and a sense-amp/writedriver. This in turn requires (1) a very large charge pump consuming: ∼20% of PCM chip space, ∼50% of latency of write operations, and ∼2× more power than a write operation itself; and (2) a large current sense-amp with long time to pre-charge the interconnect path. Then, we propose Low-Latency PCM (LLPCM) architecture. Our analysis shows that LL-PCM can give 119% higher performance and consume 43% lower memory energy than PCM for memory-intensive applications. LL-PCM is only ∼1% larger than PCM, as the cost of reducing the resistance/capacitance of the interconnect path is negated by its 4.1× smaller charge pump.

Original languageEnglish (US)
Title of host publicationProceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
StatePublished - Jun 2 2019
Event56th Annual Design Automation Conference, DAC 2019 - Las Vegas, United States
Duration: Jun 2 2019Jun 6 2019

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference56th Annual Design Automation Conference, DAC 2019
Country/TerritoryUnited States
CityLas Vegas


  • DRAM
  • Heterogeneous memory system
  • PCM

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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