Discrete range searching primitive for the GPU and its applications

Author:

Soman Jyothish1,Kothapalli Kishore2,Narayanan P. J.2

Affiliation:

1. IBM India Research Labs, New Delhi, India

2. International Institute of Information Technology, Hyderabad, India

Abstract

Graphics processing units (GPUs) provide large computational power at a very low price, which position GPUs well as an ubiquitous accelerator. However, GPUs are space constrained, and hence applications developed for GPUs are space sensitive. Space-constrained computational devices such as GPUs can greatly benefit from representations that reduce space consumption drastically. One such representation is the succinct representation of trees. Succinct representation of trees generally allows for operations such as parent queries, least common ancestor queries, and so on. Mapping such a robust representation to the GPU for targeted applications can lead to substantial improvement in problem sizes that are processed at a given point of time. Space-saving methods such as succinct data structures remain largely unexplored on the GPU. In this work, a succinct representation of ordered trees on the GPU is explored, with application to discrete range searching (DRS). Based on the succinct representations found applicable, a space--saving solution for DRS is presented here. In our method, DRS is mapped to a least common ancestor query on a Cartesian tree. For space-efficient DRS queries, we store the succinct representation of the Cartesian tree of an array. Our method uses a maximum of 7.5 bits of additional space per element. Furthermore, the speed-up achieved by our method is in the range of 20--25 for preprocessing and 25--35 for batch querying over a sequential implementation. Compared to an 8-threaded implementation, our preprocessing and querying methods obtain a speed-up of 6--8. We also study the applications of the DRS on the GPU. Efficient primitives expand the range of applications performed on the GPU. DRS is one such primitive with direct applications to string processing, document and text retrieval systems, and least common ancestor queries. We suggest that graph algorithms that use the least common ancestor, can be enabled on the GPU based on DRS primitive. We also show some applications of DRS in tree queries and string querying.

Publisher

Association for Computing Machinery (ACM)

Subject

Theoretical Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A hybrid CPU/GPU approach for optimizing sorting throughput;Parallel Computing;2019-07

2. Engineering a high-performance GPU B-Tree;Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming;2019-02-16

3. Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs;Proceedings of the 2018 International Conference on Supercomputing;2018-06-12

4. Efficient Multicore Algorithms For Identifying Biconnected Components;International Journal of Networking and Computing;2016

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