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Research Article · Open access · Published 28 April 2018

Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL

Ercan Canhasi1

Journal of Computer Science, Volume 14, Issue 5, pp. 699–704 · doi.org/10.3844/jcssp.2018.699.704

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Abstract

Discovering identical or near-identical items is urgently important in many applications such as Web crawling since it drastically reduces the text processing costs. Simhash is a widely used technique, able to attribute a bit-string identity to a text, such that similar texts have similar identities. In this study, a real-time solution for a simhash calculation in OpenCL is presented. We also show how it can be utilized by multi-CPUs, GPUs and FPGAs. As a result we indicate that the bottom line computation realized on the FPGA through OpenCL provides significant power advantages.

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Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

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Canhasi, E. (2018). Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL. Journal of Computer Science, 14(5), 699–704. https://doi.org/10.3844/jcssp.2018.699.704

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Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCLJournal of Computer Science · Volume 14, Issue 5 · pp. 699–704 · CC BY 3.0Download