GPU-accelerated predicate evaluation on column store

Authors:
Ren Wu;Bin Zhang;Meichun Hsu;Qiming Chen
Affiliations:
HP Labs, Hewlett-Packard Company, Palo Alto, CA;HP Labs, Hewlett-Packard Company, Palo Alto, CA;HP Labs, Hewlett-Packard Company, Palo Alto, CA;HP Labs, Hewlett-Packard Company, Palo Alto, CA
Venue:
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Year:
2010

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Abstract

Column scan, or predicate evaluation and filtering over a column of data in a database table, is an important primitive for data mining and data warehousing. In this paper, we present our study on accelerating column scan using a massively parallel accelerator. With a design that takes full advantage of the characteristics of the memory hierarchy and parallel execution in such processors, we have achieved very attractive speedup performance that significantly exceeds previously reported results, making the use of such an accelerator for this type of primitives much more viable. Running on a general purpose graphic processor unit (GPGPU), NVidia GTX 280 GPU, the GPU version is about 5-6 times faster than an implementation on an eight-core CPU, or over 40 times faster than that on a single-core CPU.