A General SIMD-based Approach to Accelerating Compression Algorithms [r-libre/585]

Zhao, Wayne Xin; Zhang, Xudong; Lemire, Daniel; Shan, Dongdong; Nie, Jian-Yun; Yan, Hongfei et Wen, Ji-Rong (2015). A General SIMD-based Approach to Accelerating Compression Algorithms. ACM Transactions on Information Systems, 33 (3). https://doi.org/10.1145/2735629

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Catégorie de document :	Articles de revues
Évaluation par un comité de lecture :	Oui
Étape de publication :	Publié
Résumé :	Compression algorithms are important for data oriented tasks, especially in the era of Big Data. Modern processors equipped with powerful SIMD instruction sets, provide us an opportunity for achieving better compression performance. Previous research has shown that SIMD-based optimizations can multiply decoding speeds. Following these pioneering studies, we propose a general approach to accelerate compression algorithms. By instantiating the approach, we have developed several novel integer compression algorithms, called Group-Simple, Group-Scheme, Group-AFOR, and Group-PFD, and implemented their corresponding vectorized versions. We evaluate the proposed algorithms on two public TREC datasets, a Wikipedia dataset and a Twitter dataset. With competitive compression ratios and encoding speeds, our SIMD-based algorithms outperform state-of-the-art non-vectorized algorithms with respect to decoding speeds.
Adresse de la version officielle :	http://doi.acm.org/10.1145/2735629
Déposant:	Lemire, Daniel
Responsable :	Daniel Lemire
Dépôt :	06 févr. 2015 13:43
Dernière modification :	16 juill. 2015 00:46

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