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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/1907.08817 |
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| _version_ | 1866913609739665408 |
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| author | Zhu, Xiaoke Zhang, Qi Zhou, Wei Liu, Ling |
| author_facet | Zhu, Xiaoke Zhang, Qi Zhou, Wei Liu, Ling |
| contents | In this paper, we present a neural network-enabled data distribution aware sorting method, coined as NN-sort. Our approach explores the potential of developing deep learning techniques to speed up large-scale sort operations, enabling data distribution aware sorting as a deep learning service. Compared to traditional pairwise comparison-based sorting algorithms, which sort data elements by performing pairwise operations, NN-sort leverages the neural network model to learn the data distribution and uses it to map large-scale data elements into ordered ones. Our experiments demonstrate the significant advantage of using NN-sort. Measurements on both synthetic and real-world datasets show that NN-sort yields 2.18x to 10x performance improvement over traditional sorting algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1907_08817 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Deep Learning Service for Efficient Data Distribution Aware Sorting Zhu, Xiaoke Zhang, Qi Zhou, Wei Liu, Ling Data Structures and Algorithms In this paper, we present a neural network-enabled data distribution aware sorting method, coined as NN-sort. Our approach explores the potential of developing deep learning techniques to speed up large-scale sort operations, enabling data distribution aware sorting as a deep learning service. Compared to traditional pairwise comparison-based sorting algorithms, which sort data elements by performing pairwise operations, NN-sort leverages the neural network model to learn the data distribution and uses it to map large-scale data elements into ordered ones. Our experiments demonstrate the significant advantage of using NN-sort. Measurements on both synthetic and real-world datasets show that NN-sort yields 2.18x to 10x performance improvement over traditional sorting algorithms. |
| title | Deep Learning Service for Efficient Data Distribution Aware Sorting |
| topic | Data Structures and Algorithms |
| url | https://arxiv.org/abs/1907.08817 |