Block recycling schemes and their cost-based optimization in nand flash memory based storage system

Lee, Jongmin; Kim, Sung Hoon; Kwon, Hunki; Hyun, Choulseung; Ahn, Sung Tae; Choi, Jongmoo; Lee, Dong-Hee; Noh, Sam H.

doi:10.1145/1289927.1289956

Cited by 20 publications

(9 citation statements)

References 8 publications

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“…Semi-random writes do not require moving any unmodified page to the newly allocated block, resulting in a performance comparable to sequential writes. In many other existing FTLs, modified pages are temporarily maintained in logs; logged pages, along with unmodified pages in the same block, are later copied to newly allocated blocks [13]. With this strategy as well, semi-random writes do not require copying any unmodified pages across blocks, resulting in superior performance.…”

Section: Semi-random Writesmentioning

confidence: 99%

Online maintenance of very large random samples on flash storage

Nath

Gibbons

2008

Proc. VLDB Endow.

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Recent advances in flash media have made it an attractive alternative for data storage in a wide spectrum of computing devices, such as embedded sensors, mobile phones, PDA's, laptops, and even servers. However, flash media has many unique characteristics that make existing data management/analytics algorithms designed for magnetic disks perform poorly with flash storage. For example, while random (page) reads are as fast as sequential reads, random (page) writes and in-place data updates are orders of magnitude slower than sequential writes. In this paper, we consider an important fundamental problem that would seem to be particularly challenging for flash storage: efficiently maintaining a very large (100 MBs or more) random sample of a data stream (e.g., of sensor readings). First, we show that previous algorithms such as reservoir sampling and geometric file are not readily adapted to flash. Second, we propose B-FILE, an energy-efficient abstraction for flash media to store self-expiring items, and show how a B-FILE can be used to efficiently maintain a large sample in flash. Our solution is simple, has a small (RAM) memory footprint, and is designed to cope with flash constraints in order to reduce latency and energy consumption. Third, we provide techniques to maintain biased samples with a B-FILE and to query the large sample stored in a B-FILE for a subsample of an arbitrary size. Finally, we present an evaluation with flash media that shows our techniques are several orders of magnitude faster and more energy-efficient than (flash-friendly versions of) reservoir sampling and geometric file. A key finding of our study, of potential use to many flash algorithms beyond sampling, is that "semi-random" writes (as defined in the paper) on flash cards are over two orders of magnitude faster and more energy-efficient than random writes.

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Section: Semi-random Writesmentioning

confidence: 99%

Online maintenance of very large random samples on flash storage

Nath

Gibbons

2008

Proc. VLDB Endow.

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“…A read or write can be performed on a sub-block granularity (called page). Each block is a collection of pages which can range in size from 512 bytes to 4 KB with an additional out-of-band spare region to store metadata such as mapping information for recovery, ECC information, erase counts, and valid bit [3], [13], [14]. While Flash-based SSDs may offer an order of magnitude in improved read performance over mechanical disks, there are several critical limitations with respect to writes.…”

Section: Background and Related Workmentioning

confidence: 99%

“…MLCs can provide better storage density, but they have lower lifetimes and performance in comparison to SLCs [1], [17]. In SLCs, reads and writes can be performed at speeds of 25 µsecs and 300 µsecs, respectively, while MLCs take somewhat longer [3], [13]. Lifetimes for SLCs are reported to be anywhere from 100,000 to 1,000,000 erase cycles while MLC lifetimes are typically an order of magnitude less [18], [19].…”

Section: Background and Related Workmentioning

confidence: 99%

A performance evaluation of scientific I/O workloads on Flash-based SSDs

Park

Shen

2009

2009 IEEE International Conference on Cluster Computing and Workshops

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Abstract-Flash-based solid state disks (SSDs) are an alternative form of storage device that promises to deliver higher performance than the traditional mechanically rotating hard drives. While SSDs have seen utilization in embedded, consumer, and server computer systems, there has been little understanding of its performance effects with scientific I/O workloads. This paper provides a trace driven performance evaluation of scientific I/O workloads on SSDs. We find that SSDs only provide modest performance gains over mechanical hard drives due to the writeintensive nature of many scientific workloads. Other workloads (like read-mostly web servers) would likely see much larger gains. Additionally, we observe that the concurrent I/O (when multiple parallel processes simultaneously access a single storage device) may significantly affect the SSD performance. However, such effects appear to be dependent on specific SSD implementation features and they are hard to predict in a general fashion. These results suggest that abundant cautions are needed when supporting high-performance scientific I/O workloads on Flashbased SSDs.

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“…This approach is very effective for tuning flash storage systems to the characteristic of workloads. However, most existing FTL schemes [17][18][19][20][21][22][23][24][25] assume that there is no information about BML policies or there is no buffer cache. Because write patterns are entirely changed through BML before reaching FTL, it is necessary to develop FTL algorithms that consider the BML policies.…”

Section: Introductionmentioning

confidence: 99%

Co-optimization of buffer layer and FTL in high-performance flash-based storage systems

Shim

Jung

Kim

et al. 2010

Des Autom Embed Syst

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NAND flash-based storage devices have rapidly improved their position in the secondary storage market ranging from mobile embedded systems to personal computer and enterprise storage systems. Recently, the most important issue of NAND flash-based storage systems is the performance of random writes as well as sequential writes, which strongly depends on their two main software layers: a Buffer Management Layer (BML) and a Flash Translation Layer (FTL). The primary goal of our study is to highly improve the overall performance of NAND flash-based storage systems by exploiting the cooperation between those two layers. In this paper, we propose an FTL-aware BML policy called Selective Block Padding and a BML-based FTL algorithm called Optimized Switch Merge, which overcome the limitations of existing approaches on performance enhancement. When using both the proposed techniques, evaluation results show that the throughput is significantly increased over that of previous studies.

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Block recycling schemes and their cost-based optimization in nand flash memory based storage system

Cited by 20 publications

References 8 publications

Online maintenance of very large random samples on flash storage

Online maintenance of very large random samples on flash storage

A performance evaluation of scientific I/O workloads on Flash-based SSDs

Co-optimization of buffer layer and FTL in high-performance flash-based storage systems

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