• Journal of KIISE
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• v.41 no.9
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• pp.611-616
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• 2014

Rabin fingerprinting used for chunking requires the largest amount computation time in data deduplication, In this paper, therefore, we proposed parallel Rabin fingerprinting on GPGPU for efficient data deduplication. In addition, for efficient parallelism in Rabin fingerprinting, four issues are considered. Firstly, when dividing input data stream into data sections, we consider the data located near the boundaries between data sections to calculate Rabin fingerprint continuously. Secondly, we consider exploiting the characteristics of Rabin fingerprinting for efficient operation. Thirdly, we consider the chunk boundaries which can be changed compared to sequential Rabin fingerprinting when adapting parallel Rabin fingerprinting. Finally, we consider optimizing GPGPU memory access. Parallel Rabin fingerprinting on GPGPU shows 16 times and 5.3 times better performance compared to sequential Rabin fingerprinting on CPU and compared to parallel Rabin fingerprinting on CPU, respectively. These throughput improvement of Rabin fingerprinting can lead to total performance improvement of data deduplication.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.460-463
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• 2008

현재의 스토리지 시스템 및 백업 시스템에서 중복된 데이터의 증가로 인한 문제가 점점 대두되고 있다. 이러한 중복 데이터를 검사하거나 파일의 유사성을 검사하는 데에는 BSW알고리즘이 많이 사용되고 있으며 이 BSW알고리즘 내에서 해시 값을 구하는데에는 Rabin's Fingerprint알고리즘이 일반적으로 사용되고 있다. 본 논문에서는 Rabin's Fingerprint알고리즘에 비해 보다 빠르고 간단한 Modulo-K알고리즘을 제안하며 BSW알고리즘에서 Rabin's Fingerprint를 대체함으로써 최종적으로 BSW알고리즘의 속도를 향상 시킬 수 있는 Modulo-K알고리즘을 제안한다.