An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases
Proceedings of the 17th International Conference on Data Engineering
Using multiple indexes for efficient subsequence matching in time-series databases
Information Sciences: an International Journal
Scaling and time warping in time series querying
The VLDB Journal — The International Journal on Very Large Data Bases
Proceedings of the VLDB Endowment
The VLDB Journal — The International Journal on Very Large Data Bases
A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Searching and mining trillions of time series subsequences under dynamic time warping
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Accelerating frequent item counting with FPGA
Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays
Instruction set extensions for dynamic time warping
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
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Subsequence search, especially subsequence similarity search, is one of the most important subroutines in time series data mining algorithms, and there is increasing evidence that Dynamic Time Warping (DTW) is the best distance metric. However, in spite of the great effort in software speedup techniques, including early abandoning strategies, lower bound, indexing, computation-reuse, DTW still cost too much time for many applications, e.g. 80% of the total time. Since DTW is a 2-Dimension sequential dynamic search with quite high data dependency, it is hard to use parallel hardware to accelerate it. In this work, we propose a novel framework for FPGA based subsequence similarity search and a novel PE-ring structure for DTW calculation. This framework utilizes the data reusability of continuous DTW calculations to reduce the bandwidth and exploit the coarse-grain parallelism; meanwhile guarantees the accuracy with a two-phase precision reduction. The PE-ring supports on-line updating patterns of arbitrary lengths, and utilizes the hard-wired synchronization of FPGA to realize the fine-grained parallelism. It also achieves flexible parallelism degree to do performance-cost trade-off. The experimental results show that we can achieve several orders of magnitude speedup in accelerating subsequence similarity search compared with the best software and current GPU/FPGA implementations in different datasets.