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Characterization of Android Memory References and Implication to Hybrid Memory Management

Title
Characterization of Android Memory References and Implication to Hybrid Memory Management
Authors
Lee, SoyoonBahn, Hyokyung
Ewha Authors
반효경
SCOPUS Author ID
반효경scopus
Issue Date
2021
Journal Title
IEEE ACCESS
ISSN
2169-3536JCR Link
Citation
IEEE ACCESS vol. 9, pp. 60997 - 61009
Keywords
Nonvolatile memoryRandom access memoryMemory managementSocial networking (online)Performance evaluationFocusingBrowsersAndroidsmartphoneapplicationmemory referenceNVMwrite operationhybrid memory
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Indexed
SCIE; SCOPUS WOS
Document Type
Article
Abstract
In this article, we analyze Android applications' memory reference behaviors, and observe that smartphone memory accesses are different from traditional computer systems with respect to the following five aspects: 1) A limited number of hot pages account for a majority of memory writes, and these hot pages have similar logical addresses regardless of application types; 2) The identities of these hot pages are shared library, linker, and stack regions; 3) The memory access behaviors of hot pages do not change significantly as time progresses even after applications finish their launching; 4) The skewness of memory write accesses in Android is extremely stronger than that of desktop systems; 5) In predicting re-reference likelihood of hot pages, temporal locality is better than reference frequency. Based on these observations, we present a new smartphone memory management scheme for DRAM-NVM hybrid memory. Adopting NVM is effective in power-saving of smartphones, but NVM has weaknesses in write operations. Thus, we aim to identify write-intensive pages and place them on DRAM. Unlike previous studies, we prevent migration of pages between DRAM and NVM, which eliminates unnecessary NVM write traffic that accounts for 32-42% of total write traffic. By judiciously managing the admission of hot pages in DRAM, our scheme reduces the write traffic to NVM by 42% on average without performance degradations.
DOI
10.1109/ACCESS.2021.3074179
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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