HeterMM: applying in-DRAM index to heterogeneous memory-based key-value stores

  • Yunhong Ji
  • , Wentao Huang
  • , Xuan Zhou*
  • *Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

1 Scopus citations

Abstract

We propose HeterMM, a versatile framework that leverages in-DRAM indexes in KV stores on heterogeneous memory. HeterMM incorporates a plug-in programming model, allowing for the integration of various types of indexes. By prioritizing the maintenance of both index and hot data in DRAM, HeterMM maximizes the utilization of the superior performance of DRAM. Our evaluation demonstrates that HeterMM outperforms existing state-of-the-art frameworks that convert in-DRAM indexes to persistent ones. Furthermore, HeterMM can surpass NVM-specific KV stores by carefully selecting the appropriate index for specific scenarios.

Original languageEnglish
Article number184612
JournalFrontiers of Computer Science
Volume18
Issue number4
DOIs
StatePublished - Aug 2024

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