高级命令和分布式数据布局,增强SSD内部并行性

S. Zertal
{"title":"高级命令和分布式数据布局,增强SSD内部并行性","authors":"S. Zertal","doi":"10.1109/HPCSim.2015.7237033","DOIUrl":null,"url":null,"abstract":"SSDs have been widely deployed in different areas and become competitive storage devices even for data-intensive applications. They have important performance and endurance requirements and their internal features provide a real potential to fulfil them. The multiple and independent SSD internal components allow parallel access to data at each of the four levels (package-chip-die-plane) but it relies completely on the data layout scheme. We proposed a data layout algorithm based only on the SSD basic operations. It distributes data up to the lowest level to exploit the fine grain internal parallelism and improves the SSD performance. In this paper, we also use advanced commands available on newer SSDs and request scheduling in combination with data layout scheme to provide up to the planes parallelism, taking into account both performance and endurance. The result is a new data layout algorithn to exploit the fine grain SSD internal parallelism. It respects the rules imposed by the wise use of advanced commands and the recommandations of maintaining a wide data distribution. The results show an improvement of performance and a Write Amplification (WA) factor very close to the one using basic operations which indicates a preserved endurance.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"17 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advanced commands and distributed data layout to enhance the SSD internal parallelism\",\"authors\":\"S. Zertal\",\"doi\":\"10.1109/HPCSim.2015.7237033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SSDs have been widely deployed in different areas and become competitive storage devices even for data-intensive applications. They have important performance and endurance requirements and their internal features provide a real potential to fulfil them. The multiple and independent SSD internal components allow parallel access to data at each of the four levels (package-chip-die-plane) but it relies completely on the data layout scheme. We proposed a data layout algorithm based only on the SSD basic operations. It distributes data up to the lowest level to exploit the fine grain internal parallelism and improves the SSD performance. In this paper, we also use advanced commands available on newer SSDs and request scheduling in combination with data layout scheme to provide up to the planes parallelism, taking into account both performance and endurance. The result is a new data layout algorithn to exploit the fine grain SSD internal parallelism. It respects the rules imposed by the wise use of advanced commands and the recommandations of maintaining a wide data distribution. The results show an improvement of performance and a Write Amplification (WA) factor very close to the one using basic operations which indicates a preserved endurance.\",\"PeriodicalId\":134009,\"journal\":{\"name\":\"2015 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"17 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSim.2015.7237033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSim.2015.7237033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

ssd已广泛应用于各个领域,甚至成为数据密集型应用的有竞争力的存储设备。它们具有重要的性能和耐久性要求,其内部特性提供了满足这些要求的真正潜力。多个独立的SSD内部组件允许在四个级别(封装-芯片-模平面)中的每个级别并行访问数据,但它完全依赖于数据布局方案。提出了一种仅基于SSD基本操作的数据布局算法。它将数据分布到最低层,利用细粒度的内部并行性,提高SSD性能。在本文中,我们还使用了新ssd上可用的高级命令,并将请求调度与数据布局方案相结合,以提供最高的平面并行性,同时考虑到性能和耐用性。这是一种利用SSD内部细粒度并行性的新数据布局算法。它尊重明智地使用高级命令所施加的规则和维护广泛数据分布的建议。结果表明,性能得到了改善,写入放大(WA)因子非常接近使用基本操作的因子,这表明保留了耐久性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Advanced commands and distributed data layout to enhance the SSD internal parallelism
SSDs have been widely deployed in different areas and become competitive storage devices even for data-intensive applications. They have important performance and endurance requirements and their internal features provide a real potential to fulfil them. The multiple and independent SSD internal components allow parallel access to data at each of the four levels (package-chip-die-plane) but it relies completely on the data layout scheme. We proposed a data layout algorithm based only on the SSD basic operations. It distributes data up to the lowest level to exploit the fine grain internal parallelism and improves the SSD performance. In this paper, we also use advanced commands available on newer SSDs and request scheduling in combination with data layout scheme to provide up to the planes parallelism, taking into account both performance and endurance. The result is a new data layout algorithn to exploit the fine grain SSD internal parallelism. It respects the rules imposed by the wise use of advanced commands and the recommandations of maintaining a wide data distribution. The results show an improvement of performance and a Write Amplification (WA) factor very close to the one using basic operations which indicates a preserved endurance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Transient performance evaluation of cloud computing applications and dynamic resource control in large-scale distributed systems A security framework for population-scale genomics analysis Deep learning with shallow architecture for image classification A new reality requiers new ecosystems Investigation of DVFS based dynamic reliability management for chip multiprocessors
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1