A dynamic adaptive converter and management for PRAM-based main memory

In Sung Choi, Sung In Jang, Chang Hoon Oh, Charles C. Weems, Shin Dug Kim

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


As DRAM-based main memory becomes a dominant factor in the energy consumption and cost of any computer system, new non-volatile memory technologies have been proposed to replace DRAMs. For example, PRAM is emerged as a leading alternative for main memory technology. However, the access latency of PRAM is significantly slower than that of DRAM and an interfacing converter is required to at least partly alleviate this latency difference. The interfacing converter sits between PRAM-based main memory and the last level of cache memory. In this paper, we present a proposed dynamic adaptive converter and its management scheme for PRAM-based main memory. In addition to overcoming long access latency, it provides enhanced endurance. The adaptive converter is composed of an aggressive streaming buffer to make better use of spatial locality by dynamically varying fetch size, a write buffer to improve endurance limit, and an adaptive filtering buffer to better utilize temporal locality. Our experimental results show that we can reduce buffer miss rate by about 59%, compared with using a single buffer structure with same space. Our approach also hides PRAM access latency more effectively. It improves the number of superblocks pre-fetched from main memory by 25%. Therefore, the converter shows its effectiveness comparable to a case with larger buffer space, without expending the extra power.

Original languageEnglish
Pages (from-to)554-561
Number of pages8
JournalMicroprocessors and Microsystems
Issue number6-7
Publication statusPublished - 2013

Bibliographical note

Funding Information:
This work was supported by Samsung Co. “Design of adaptive parallel accelerator and DSP/SIMD hybrid system for high performance media applications” project.

Funding Information:
This work was supported by the Seoul R&BD Program Grant funded by Samsung Electronics ( 2012-8-1364 ).

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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