KIPS Transactions on Computer and Communication Systems (정보처리학회논문지:컴퓨터 및 통신 시스템)

Korea Information Processing Society (한국정보처리학회)
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Parallel Computation for Extended Edit Distances Using the Shared Memory on GPU

GPU의 공유메모리를 활용한 확장편집거리 병렬계산

  • 김영호 (인하대학교 컴퓨터정보공학과) ;
  • 나중채 (세종대학교 컴퓨터공학과) ;
  • 심정섭 (인하대학교 컴퓨터정보공학과)
  • Received : 2015.02.16
  • Accepted : 2015.05.07
  • Published : 2015.07.31
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Abstract

Given two strings X and Y (|X|=m, |Y|=n) over an alphabet ${\Sigma}$, the extended edit distance between X and Y can be computed using dynamic programming in O(mn) time and space. Recently, a parallel algorithm that takes O(m+n) time and O(mn) space using m threads to compute the extended edit distance between X and Y was presented. In this paper, we present an improved parallel algorithm using the shared memory on GPU. The experimental results show that our parallel algorithm runs about 19~25 times faster than the previous parallel algorithm.

알파벳 ${\Sigma}$로 구성된 길이가 각각 m, n인 두 문자열 X, Y가 주어졌을 때, X, Y의 확장편집거리는 동적프로그래밍을 이용하여 O(mn) 시간과 공간을 계산할 수 있다. 최근 m개의 쓰레드를 이용하여 O(m+n) 시간과 O(mn) 공간을 사용하여 X, Y의 확장편집거리를 계산하는 병렬알고리즘이 제시되었다. 본 논문에서는 GPU의 공유메모리를 활용하여 수행시간을 개선한 병렬알고리즘을 제시한다. 실험 결과, 개선된 병렬알고리즘이 기존의 병렬알고리즘보다 약 19~25배 이상 빠른 수행시간을 보였다.

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References

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