使用SIMD技术的超快速布隆过滤器

Jianyuan Lu, Ying Wan, Yang Li, Chuwen Zhang, Huichen Dai, Yi Wang, Gong Zhang, B. Liu
{"title":"使用SIMD技术的超快速布隆过滤器","authors":"Jianyuan Lu, Ying Wan, Yang Li, Chuwen Zhang, Huichen Dai, Yi Wang, Gong Zhang, B. Liu","doi":"10.1109/IWQoS.2017.7969125","DOIUrl":null,"url":null,"abstract":"The network link speed is increasing at an alarming rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in network applications. It also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters, by leveraging the SIMD techniques. We make three improvements for the UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we change a Bloom filter's bit-test process from sequential to parallel. Third, we increase the cache efficiency of membership check by encoding an element's information to a small block which can easily fit into a cache-line. Both theoretical analysis and extensive simulations show that the UFBF greatly exceeds the state-of-the-art Bloom filter variants on membership check speed.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Ultra-Fast Bloom Filters using SIMD techniques\",\"authors\":\"Jianyuan Lu, Ying Wan, Yang Li, Chuwen Zhang, Huichen Dai, Yi Wang, Gong Zhang, B. Liu\",\"doi\":\"10.1109/IWQoS.2017.7969125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The network link speed is increasing at an alarming rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in network applications. It also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters, by leveraging the SIMD techniques. We make three improvements for the UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we change a Bloom filter's bit-test process from sequential to parallel. Third, we increase the cache efficiency of membership check by encoding an element's information to a small block which can easily fit into a cache-line. Both theoretical analysis and extensive simulations show that the UFBF greatly exceeds the state-of-the-art Bloom filter variants on membership check speed.\",\"PeriodicalId\":422861,\"journal\":{\"name\":\"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQoS.2017.7969125\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2017.7969125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

网络链路的速度正在以惊人的速度增长,这就要求路由器/交换机的所有网络功能都能跟上。布隆滤波器是网络应用中广泛使用的一种隶属度校验数据结构。同时也面临着提高成员校验速度的迫切要求。为此,本文提出了一种新的布隆过滤器变体,称为超快速布隆过滤器,利用SIMD技术。我们对UFBF进行了三方面的改进,以加快隶属度检查的速度。首先,我们开发了一种新的哈希计算算法,该算法可以使用SIMD指令并行计算多个哈希函数。其次,我们将布隆过滤器的位测试过程从顺序更改为并行。第三,我们通过将元素的信息编码成一个小块来提高成员资格检查的缓存效率,这个小块可以很容易地放入缓存行。理论分析和大量的仿真结果表明,UFBF在成员检验速度上大大超过了最先进的布隆滤波器变体。
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
Ultra-Fast Bloom Filters using SIMD techniques
The network link speed is increasing at an alarming rate, which requires all network functions on routers/switches to keep pace. Bloom filter is a widely-used membership check data structure in network applications. It also faces the urgent demand of improving the performance in membership check speed. To this end, this paper proposes a new Bloom filter variant called Ultra-Fast Bloom Filters, by leveraging the SIMD techniques. We make three improvements for the UFBF to accelerate the membership check speed. First, we develop a novel hash computation algorithm which can compute multiple hash functions in parallel with the use of SIMD instructions. Second, we change a Bloom filter's bit-test process from sequential to parallel. Third, we increase the cache efficiency of membership check by encoding an element's information to a small block which can easily fit into a cache-line. Both theoretical analysis and extensive simulations show that the UFBF greatly exceeds the state-of-the-art Bloom filter variants on membership check speed.
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
When privacy meets economics: Enabling differentially-private battery-supported meter reporting in smart grid Task assignment with guaranteed quality for crowdsourcing platforms Social media stickiness in Mobile Personal Livestreaming service Multicast scheduling algorithm in software defined fat-tree data center networks A cooperative mechanism for efficient inter-domain in-network cache sharing
×
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