Extending SSD lifetime in database applications with page overwrites

Kaiser, Jürgen; Margaglia, Fabio; Brinkmann, André

doi:10.1145/2485732.2485747

Cited by 9 publications

(3 citation statements)

References 45 publications

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“…Other novel techniques have been proposed to make the SSD part of the memory in order to improve performance and reduce cost per gigabyte of memory. and also uses the flash‐based SSD as an extended buffer pool for database systems.…”

Section: Related Workmentioning

confidence: 99%

AMC: an adaptive multi‐level cache algorithm in hybrid storage systems

Cheng

Chen

Wang

et al. 2015

Concurrency and Computation

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SUMMARYHybrid storage systems that consist of flash-based solid state drives (SSDs) and traditional disks are now widely used. In hybrid storage systems, there exists a two-level cache hierarchy that regard dynamic random access memory (DRAM) as the first level cache and SSD as the second level cache for disk storage. However, this two-level cache hierarchy typically uses independent cache replacement policies for each level, which makes cache resource management inefficient and reduces system performance. In this paper, we propose a novel adaptive multi-level cache (AMC) replacement algorithm in hybrid storage systems. The AMC algorithm adaptively adjusts cache blocks between DRAM and SSD cache levels using an integrated solution. AMC uses combined selective promote and demote operations to dynamically determine the level in which the blocks are to be cached. In this manner, the AMC algorithm achieves multi-level cache exclusiveness and makes cache resource management more efficient. By using real-life storage traces, our evaluation shows the proposed algorithm improves hybrid multi-level cache performance and also increases the SSD lifetime compared with traditional multi-level cache replacement algorithms.

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Section: Related Workmentioning

confidence: 99%

AMC: an adaptive multi‐level cache algorithm in hybrid storage systems

Cheng

Chen

Wang

et al. 2015

Concurrency and Computation

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“…Current flash technology writes all files by applying a high programming voltage to ensure a specific data retention time, typically from one to ten years. However, such a high programming voltage will also cause severe cache damage and significantly reduce the memory lifetime [8]- [12].…”

Section: Introductionmentioning

confidence: 99%

Lifecycle-Aware Online Video Caching

Braud

et al. 2021

IEEE Trans. on Mobile Comput.

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The current explosion of video traffic compels service providers to deploy caches at edge networks. Nowadays, most caching systems store data with a high programming voltage corresponding to the largest possible 'expiry date', typically on the order of years, which maximizes the cache damage. However, popular videos rarely exhibit lifecycles longer than a couple of months. Consequently, the programming voltage can instead be adapted to fit the lifecycle and mitigate the cache damage accordingly. In this paper, we propose LiA-cache, a Lifecycle-Aware caching policy for online videos. LiA-cache finds both near-optimal caching retention times and cache eviction policies by optimizing traffic delivery cost and cache damage cost conjointly. We first investigate temporal patterns of video access from a real-world dataset covering 10 million online videos collected by one of the largest mobile network operators in the world. We next cluster the videos based on their access lifecycles and integrate the clustering into a general model of the caching system. Specifically, LiA-cache analyzes videos and caches them depending on their cluster label. Compared to other popular policies in real-world scenarios, LiA-cache can reduce cache damage up to 90%, while keeping a cache hit ratio close to a policy purely relying on video popularity.

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“…Several techniques and approaches [11,12,13] have been proposed to optimize the endurance of SSD devices under different I/O workloads, particularly the kinds of workloads produced by personal computers, web servers, database systems, etc. However, none of them tackles on SSD endurance issues in HPC environment, because the HPC I/O workloads usually consist of extremely intensive write operations which can quickly wear out the SSD devices even when cutting-edge endurance optimization techniques are used.…”

Section: Introductionmentioning

confidence: 99%

Optimizing checkpoint data placement with guaranteed burst buffer endurance in large-scale hierarchical storage systems

Wan

Cao

Wang

et al. 2017

Journal of Parallel and Distributed Computing

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Non-volatile devices, such as SSDs, will be an integral part of the deepening storage hierarchy on large-scale HPC systems. These devices can be on the compute nodes as part of a distributed burst buffer service or they can be external. Wherever they are located in the hierarchy, one critical design issue is the SSD endurance under the write-heavy workloads, such as the checkpoint I/O for scientific applications. For these environments, it is widely assumed that checkpoint operations can occur once every 60 minutes and for each checkpoint step as much as half of the system memory can be written out. Unfortunately, for large-scale HPC applications, the burst buffer SSDs can be worn out much more quickly given the extensive amount of data written at every checkpoint step. One possible solution is to control the amount of data written by reducing the checkpoint frequency. However, a direct effect caused by reduced checkpoint frequency is increased vulnerability window of system failures and therefore potentially wasted computation time, especially for large-scale compute jobs. In this paper, we propose a new checkpoint placement optimization model which collaboratively utilizes both the burst buffer and the parallel file system to store the checkpoints, with design goals of maximizing computation efficiency while guaranteeing the SSD endurance requirements. Moreover, we present

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Extending SSD lifetime in database applications with page overwrites

Cited by 9 publications

References 45 publications

AMC: an adaptive multi‐level cache algorithm in hybrid storage systems

AMC: an adaptive multi‐level cache algorithm in hybrid storage systems

Lifecycle-Aware Online Video Caching

Optimizing checkpoint data placement with guaranteed burst buffer endurance in large-scale hierarchical storage systems

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