Data Management Design for Interlaced Magnetic Recording


Fenggang Wu, Baoquan Zhang, Zhichao Cao, Hao Wen, Bingzhe Li, and Jim Diehl, University of Minnesota, Twin Cities; Guohua Wang, South China University of Technology; David H.C. Du, University of Minnesota, Twin Cities


Interlaced Magnetic Recording (IMR) is a promising technology which achieves higher data density and lower write amplification than Shingled Magnetic Recording (SMR) when used with Heat-Assisted Magnetic Recording (HAMR). In IMR, top (narrower) tracks and bottom (wider) tracks are interlaced so that each bottom track is partially overlapped with two adjacent top tracks. Top tracks can be updated without any write amplification, but updating a data block in a bottom track requires reading and rewriting of the affected data on the two neighboring top tracks if they contain valid data. We investigate efficient data management schemes for IMR in this paper. First, we design a Three-Phase data management algorithm that allocates disk space in three stages according to disk usage. We further propose two techniques, Top-Buffer and Block-Swap, which can be used in IMR to improve the performance of the Three-Phase algorithm. Top-Buffer opportunistically makes use of unallocated top track space as a buffer for updates to the bottom tracks, while Block-Swap progressively swaps hot data in bottom tracks with cold data in top tracks. Finally, we propose our Data Management design for IMR, or DM-IMR, by integrating Top-Buffer and Block-Swap with the Three-Phase scheme. Evaluations with Microsoft Research Cambridge traces show that DM-IMR can increase the throughput and reduce the write amplification for all traces when compared with the Three-Phase baseline scheme.

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@inproceedings {216882,
author = {Fenggang Wu and Baoquan Zhang and Zhichao Cao and Hao Wen and Bingzhe Li and Jim Diehl and Guohua Wang and David H.C. Du},
title = {Data Management Design for Interlaced Magnetic Recording},
booktitle = {10th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 18)},
year = {2018},
address = {Boston, MA},
url = {},
publisher = {USENIX Association},
month = jul