Abstract
Approximate string matching has been widely used in many areas, such as web searching, and deoxyribonucleic acid sequence matching, etc. Approximate string matching allows difference between a string and a pattern caused by insertion, deletion and substitution. Because approximate string matching is a data-intensive task, accelerating approximate string matching has become crucial for processing big data. In this paper, we propose a hierarchical parallelism approach to accelerate the bit-parallel algorithm on NVIDIA GPUs. A data parallelism approach is used to accelerate the kernel of the bit-parallel algorithm while a task parallelism approach is used to overlap data transfer with kernel computation. In addition, we propose to use hashing to reduce the memory usage and achieve 98.4% of memory reduction. The experimental results show that the bit-parallel algorithm performed on GPUs achieves 7 to 11 times faster than the multithreaded CPU implementation. Compared to the state-of-the-art approaches, the proposed approach achieves 2.8 to 104.8 times improvement.
Original language | English |
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Title of host publication | Proceedings - 2014 Symposium on Computer Applications and Communications, SCAC 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 76-81 |
Number of pages | 6 |
ISBN (Electronic) | 9780769553191 |
DOIs | |
Publication status | Published - 2014 Sep 29 |
Event | 2014 Symposium on Computer Applications and Communications, SCAC 2014 - Weihai, China Duration: 2014 Jul 26 → 2014 Jul 27 |
Other
Other | 2014 Symposium on Computer Applications and Communications, SCAC 2014 |
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Country | China |
City | Weihai |
Period | 2014/07/26 → 2014/07/27 |
Keywords
- approximate string matching
- bit-parallel algorithm
- graphic processing units
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications