Dissertation/Thesis Abstract

Use of GPU architecture to optimize Rabin fingerprint data chunking algorithm by concurrent programming
by Wang, Sean, M.S., California State University, Long Beach, 2016, 48; 10108186
Abstract (Summary)

Data deduplication is introduced as a popular technique used to increase storage efficiency used in various data centers and corporate backup environments. There are various caching techniques and metadata checking available to prevent excessive file scanning. Due to the nature of content addressable chunking algorithm being a serial operation, the data deduplication chunking process often times become the performance bottleneck. This project introduces a parallelized Rabin fingerprint algorithm suitable for GPU hardware architecture that aims to optimize the performance of the deduplication process.

Indexing (document details)
Advisor: Chelian, Michael
Commitee: Hoffman, Michael, Lam, Shui
School: California State University, Long Beach
Department: Computer Engineering and Computer Science
School Location: United States -- California
Source: MAI 55/04M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Computer science
Keywords: Content addressable storage, Cuda, Deduplication, GPUs, Rabin fingerprint
Publication Number: 10108186
ISBN: 9781339715490
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