Global Clean Page First Replacement and Index-Aware Multistream Prefetcher in Hybrid Memory Architecture

Ing Chao Lin, Da Wei Chang, Wei Jun Chen, Jian Ting Ke, Po Han Huang

Research output: Contribution to journalArticlepeer-review


As cloud computing and big data applications become more popular, the demand for large capacity memory and data preservation in memory increases. Therefore, nonvolatile memory (NVM) with high capacity is being actively developed. A hybrid memory that comprises both NVM and DRAM and provides both high access speed and nonvolatility has become a major trend. However, compared to DRAM, NVM in the hybrid memory typically suffers from a shorter lifetime and higher latency. To improve the lifetime and address the latency issues associated with hybrid memory, we propose a global clean page first replacement (GCPF) to reduce the write operations to NVM. We also propose an index-aware multistream prefetcher (IAMSP) that considers the indexes of prefetch candidates individually so as to prefetch pages from NVM more accurately. Benchmarks with a large memory footprint are used to evaluate the proposed schemes. The experimental results show that GCPF enhances lifetime by 56.8% as compared to LRU, on average. When applying prefetching schemes on GCPF, the lifetime is insignificantly degraded. In addition, IAMSP reduces DRAM misses by 42.0% as compared to LRU, while a modern prefetcher that can change the prefetch degree dynamically only reduces DRAM misses by 38.0%, on average. When applying both GCPF and IAMSP, the average access latency can be reduced by 28.8% as compared to LRU.

Original languageEnglish
Article number8756031
Pages (from-to)1750-1763
Number of pages14
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number9
Publication statusPublished - 2020 Sept

All Science Journal Classification (ASJC) codes

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


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