GPU-Accelerated Predicate Evaluation on Column Store
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.
Parallel Algorithm Scan Predicate evaluation Graphics Processor GPGPU Accelerator Multi-core Many-core Data parallelism
Ren Wu Bin Zhang Meichun Hsu Qiming Chen
HP Labs, Hewlett-Packard Company, 1501 Page Mill Road, Palo Alto, CA 94304, USA
国际会议
11th International Conference,WAIM 2010(第十一届网络时代管理国际会议)
九寨沟
英文
570-581
2010-07-14（万方平台首次上网日期，不代表论文的发表时间）