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Non-volatile main memory management methods based on a file system

Overview of attention for article published in SpringerPlus, September 2014
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Title
Non-volatile main memory management methods based on a file system
Published in
SpringerPlus, September 2014
DOI 10.1186/2193-1801-3-494
Pubmed ID
Authors

Shuichi Oikawa

Abstract

There are upcoming non-volatile (NV) memory technologies that provide byte addressability and high performance. PCM, MRAM, and STT-RAM are such examples. Such NV memory can be used as storage because of its data persistency without power supply while it can be used as main memory because of its high performance that matches up with DRAM. There are a number of researches that investigated its uses for main memory and storage. They were, however, conducted independently. This paper presents the methods that enables the integration of the main memory and file system management for NV memory. Such integration makes NV memory simultaneously utilized as both main memory and storage. The presented methods use a file system as their basis for the NV memory management. We implemented the proposed methods in the Linux kernel, and performed the evaluation on the QEMU system emulator. The evaluation results show that 1) the proposed methods can perform comparably to the existing DRAM memory allocator and significantly better than the page swapping, 2) their performance is affected by the internal data structures of a file system, and 3) the data structures appropriate for traditional hard disk drives do not always work effectively for byte addressable NV memory. We also performed the evaluation of the effects caused by the longer access latency of NV memory by cycle-accurate full-system simulation. The results show that the effect on page allocation cost is limited if the increase of latency is moderate.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 35%
Student > Ph. D. Student 3 18%
Researcher 2 12%
Student > Doctoral Student 2 12%
Student > Bachelor 1 6%
Other 0 0%
Unknown 3 18%
Readers by discipline Count As %
Computer Science 12 71%
Physics and Astronomy 1 6%
Unknown 4 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 September 2014.
All research outputs
#17,725,418
of 22,761,738 outputs
Outputs from SpringerPlus
#1,203
of 1,852 outputs
Outputs of similar age
#159,577
of 237,234 outputs
Outputs of similar age from SpringerPlus
#74
of 104 outputs
Altmetric has tracked 22,761,738 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 237,234 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.