Institute of Computing Technology, Chinese Academy IR
NetSHa: In-Network Acceleration of LSH-Based Distributed Search | |
Zhang, Penghao1,2; Pan, Heng1,3; Li, Zhenyu1,3; Cui, Penglai1,2; Jia, Ru1,2; He, Peng4; Zhang, Zhibin1; Tyson, Gareth5; Xie, Gaogang6 | |
2022-09-01 | |
发表期刊 | IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS |
ISSN | 1045-9219 |
卷号 | 33期号:9页码:2213-2229 |
摘要 | Locality Sensitive Hashing (LSH) is widely adopted to index similar data in high-dimensional space for approximate nearest neighbor search. Demanding applications (e.g. web search) mean that LSH must exhibit low response times and high throughput. To achieve this, they tend to load balance between multiple machines. However, as the scale of concurrent queries and the volume of data grow, large numbers of index messages are required. Hence, the network is a key bottleneck. To address this gap, we propose NetSHa, which exploits the computational capacity of programmable switches. Specifically, we introduce a heuristic sort-reduce approach to drop potentially poor candidate answers while preserving search quality. Then, NetSHa aggregates good candidate answers from different index messages when transmitting them. Through this, it reduces the network communication cost. Furthermore, we introduce a best-effort replacement mechanism to improve its concurrency. We implement NetSHa on a Barefoot Tofino programmable switch and evaluate it using 7 real-world datasets. The experimental results show that NetSHa reduces the packet volume by 4 similar to 10 times and improves the search efficiency by least 3x in comparison with typical LSH-based distributed search frameworks. |
关键词 | Servers Indexes Costs Task analysis Hash functions Concurrent computing Aggregates Local sensitive hashing distributed search in-network computation |
DOI | 10.1109/TPDS.2021.3135842 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2020YFB1805600] ; National Natural Science Foundation of China[61725206] ; National Natural Science Foundation of China[U20A20180] ; National Natural Science Foundation of China[62002344] ; Informatization Plan of Chinese Academy of Sciences[CAS-WX2021SF-0506] ; CAS-Austria Joint Project[171111KYSB20200001] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000757848700004 |
出版者 | IEEE COMPUTER SOC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/18985 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Li, Zhenyu; Xie, Gaogang |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Purple Mt Labs, Nanjing 211111, Peoples R China 4.ByteDance Inc, Beijing 100089, Peoples R China 5.Queen Mary Univ London, London E1 4NS, England 6.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100045, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Penghao,Pan, Heng,Li, Zhenyu,et al. NetSHa: In-Network Acceleration of LSH-Based Distributed Search[J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,2022,33(9):2213-2229. |
APA | Zhang, Penghao.,Pan, Heng.,Li, Zhenyu.,Cui, Penglai.,Jia, Ru.,...&Xie, Gaogang.(2022).NetSHa: In-Network Acceleration of LSH-Based Distributed Search.IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,33(9),2213-2229. |
MLA | Zhang, Penghao,et al."NetSHa: In-Network Acceleration of LSH-Based Distributed Search".IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 33.9(2022):2213-2229. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论