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Decoding billions of integers per second through vectorization [r-libre/193]

Lemire, Daniel, & Boytsov, Leonid (2015). Decoding billions of integers per second through vectorization. Software: Practice & Experience, 45 (1), 1-29. https://doi.org/10.1002/spe.2203

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License : Creative Commons Attribution.
Item Type: Journal Articles
Refereed: Yes
Status: Published
Abstract: In many important applications—such as search engines and relational database systems—data are stored in the form of arrays of integers. Encoding and, most importantly, decoding of these arrays consumes considerable CPU time. Therefore, substantial effort has been made to reduce costs associated with compression and decompression. In particular, researchers have exploited the superscalar nature of modern processors and single-instruction, multiple-data (SIMD) instructions. Nevertheless, we introduce a novel vectorized scheme called SIMD-BP128⋆ that improves over previously proposed vectorized approaches. It is nearly twice as fast as the previously fastest schemes on desktop processors (varint-G8IU and PFOR). At the same time, SIMD-BP128⋆ saves up to 2 bits/int. For even better compression, we propose another new vectorized scheme (SIMD-FastPFOR) that has a compression ratio within 10% of a state-of-the-art scheme (Simple-8b) while being two times faster during decoding.
Official URL: http://onlinelibrary.wiley.com/doi/10.1002/spe.220...
Depositor: Lemire, Daniel
Owner / Manager: Daniel Lemire
Deposited: 14 Jul 2014 20:13
Last Modified: 02 Mar 2021 18:58

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