UM
Exploit Every Cycle: Vectorized Time Series Algorithms on Modern Commodity CPUs
Tang, Bo; Yiu, Man Lung; Li, Yuhong; Hou, Leong U.; Blanas, S; Bordawekar, R; Lahiri, T; Levandoski, J; Pavlo, A
2017
Conference NameDATA MANAGEMENT ON NEW HARDWARE
Volume10195
Pages18-39
Publication PlaceGEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
PublisherSPRINGER INTERNATIONAL PUBLISHING AG
AbstractMany time series algorithms reduce the computation cost by pruning unpromising candidates with lower-bound distance functions. In this paper, we focus on an orthogonal research direction that further boosts the performance by unlocking the potentials of modern commodity CPUs. First, we conduct a performance profiling on existing algorithms to understand where does time go. Second, we design vectorized implementations for lower-bound and distance functions that can enjoy characteristics (e.g., data parallelism, caching, branch prediction) provided by CPU. Third, our vectorized methods are general and applicable to many time series problems such as subsequence search, motif discovery and kNN classification. Our experimental study on real datasets shows that our proposal can achieve up to 6 times of speedup.
DOI10.1007/978-3-319-56111-0_2
URLView the original
Indexed ByCPCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000425841900002
The Source to ArticleWOS
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Document TypeConference paper
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Tang, Bo,Yiu, Man Lung,Li, Yuhong,et al. Exploit Every Cycle: Vectorized Time Series Algorithms on Modern Commodity CPUs[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2017:18-39.
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