Endurance Enhancement of Flash-Memory Storage, Systems: An Efficient Static Wear Leveling Design

Chang, Yuan-Hao; Hsieh, Jen-Wei; Kuo, Tei-Wei

doi:10.1109/dac.2007.375155

Cited by 62 publications

(83 citation statements)

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“…Each memory cell typically has a lifetime of 10 3 -10 9 erase operations [10]. Wear-leveling techniques are used to delay the wear-out of the first flash block by spreading erases evenly across the blocks [17], [5].…”

Section: Introductionmentioning

confidence: 99%

A semi-preemptive garbage collector for solid state drives

Lee

Kim

Shipman

et al. 2011

(Ieee Ispass) Ieee International Symposium on Performance Analysis of Systems and Software

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Abstract-NAND flash memory is a preferred storage media for various platforms ranging from embedded systems to enterprise-scale systems. Flash devices do not have any mechanical moving parts and provide low-latency access. They also require less power compared to rotating media. Unlike hard disks, flash devices use out-of-update operations and they require a garbage collection (GC) process to reclaim invalid pages to create free blocks. This GC process is a major cause of performance degradation when running concurrently with other I/O operations as internal bandwidth is consumed to reclaim these invalid pages. The invocation of the GC process is generally governed by a low watermark on free blocks and other internal device metrics that different workloads meet at different intervals. This results in I/O performance that is highly dependent on workload characteristics. In this paper, we examine the GC process and propose a semi-preemptive GC scheme that can preempt on-going GC processing and service pending I/O requests in the queue. Moreover, we further enhance flash performance by pipelining internal GC operations and merge them with pending I/O requests whenever possible. Our experimental evaluation of this semi-preemptive GC sheme with realistic workloads demonstrate both improved performance and reduced performance variability. Write-dominant workloads show up to a 66.56% improvement in average response time with a 83.30% reduced variance in response time compared to the non-preemptive GC scheme.

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Section: Introductionmentioning

confidence: 99%

A semi-preemptive garbage collector for solid state drives

Lee

Kim

Shipman

et al. 2011

(Ieee Ispass) Ieee International Symposium on Performance Analysis of Systems and Software

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“…Early work focused on how to assemble flash chips to simulate traditional hard disks [9], [5], [10] and how to extend the lifetime of flash disks [4], [6], [10]. Based on these research efforts, recent work have exploited the characteristics of flash disks to enhance the performance of RDBMSs.…”

Section: Related Workmentioning

confidence: 99%

“…For instance, flash-based storage does not involve any mechanical components and hence there is a negligible seek time and rotational delay in reading or writing a page on a flash disk. While flash disks still have some overhead on each I/O operation, which is caused by the encapsulated logic for such purposes as wear leveling and internal caching [4], [6], such overhead can be more than 20 times smaller than its mechanical counterpart in magnetic disks. Recall that query processing algorithms on magnetic disks often spend an effort to avoid random I/O operations but exploit sequential I/O operations whenever possible.…”

Section: Introductionmentioning

confidence: 99%

DigestJoin: Exploiting Fast Random Reads for Flash-Based Joins

Liu

et al. 2009

2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware

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Abstract-Flash disks have been an emerging secondary storage media. In particular, there have been portable devices, multimedia players and laptop computers that are configured with no magnetic disks but flash disks. It is envisioned that some RDBMSs will operate on flash disks in the near future. However, the I/O characteristics of flash disks are different from those of magnetic disks. Thus, in this paper, we study the core of query processing in RDBMSs -join processing -on flash disks. Specifically, we propose a new join method, called DigestJoin, to exploit fast random reads of flash disks. DigestJoin consists of two phases: (1) projecting the join attributes followed by a join on the projected attributes; and (2) fetching the full tuples that satisfy the join to produce the final join results. While the problem of tuple/page fetching with minimum I/O cost (in the second phase) is intractable, we propose three heuristic fetching strategies. We have implemented DigestJoin on a real flash disk for performance evaluation. Experiments on TPC-H datasets show that DigestJoin clearly outperforms the traditional sort-merge join under various system configurations.

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“…If the same block is erased and then re-programmed every second, the block would exceed the 10,000 cycle limit in just three hours. Thus, wear-leveling policy that wears down all memory blocks as evenly as possible is necessary [14,15].…”

Section: Flash Memory Characteristicsmentioning

confidence: 99%