OLAP star connection query optimizing method under CPU and GPU mixing framework

A technology for connecting queries and optimizing methods, applied in the field of database management, can solve problems such as speeding up memory big data OLAP query processing performance, and achieve the effect of improving access efficiency and query processing performance

Active Publication Date: 2013-09-18
RENMIN UNIVERSITY OF CHINA
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Problems solved by technology

[0006] But as far as the inventor knows, there is no research on using GPU cache as an index storage engine to accelerate the performance of OLAP query processing of memory big data

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  • OLAP star connection query optimizing method under CPU and GPU mixing framework
  • OLAP star connection query optimizing method under CPU and GPU mixing framework
  • OLAP star connection query optimizing method under CPU and GPU mixing framework

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Embodiment Construction

[0026] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0027] According to relevant research, GPU and CPU are equivalent to a distributed system connected by PCI-E bus, in which GPU has a limited high-speed cache, which is suitable for high-speed parallel processing on simple data types, but it is necessary to further reduce the communication between CPU and GPU. data transfer cost. The GPU cache capacity is small, but the data access performance is high, and it is suitable for storing indexes that can accelerate multi-table join operations. As mentioned earlier, many-core coprocessors have become the basic platform for high-performance computing. At present, many-core coprocessors are mainly based on NVIDIA's general-purpose GPU and Intel's Xeon Phi TM coprocessor is represented by the With 2688 processing cores, 250GB / s memory bandwidth and 6GB memory; Xeon Phi TM The coprocessor...

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Abstract

The invention discloses an OLAP (On-Line Analytical Processing) star connection query optimizing method under a CPU (Central Processing Unit) and GPU (Graphics Processing Unit) mixing framework. The method comprises the following steps: first filtering and optimizing an OLAP star connection operation through bitmap connection indexing, buffering high-frequently accessed connecting bitmap in a GPU buffer memory, next, loading fact table external key attribute group satisfying the connecting bitmap filtering condition into the GPU buffer memory to carry out star connection filtering, and finally switching the whole table scanning of the big fact table of the internal memory into accessing randomly according to the position through filtering bitmap generated by the GPU, thereby improving the querying and treating performances of the OLAP star connection. The method improves the storage efficiency of the GPU buffer memory and the parallel processing efficiency of the GPU, and improves the OLAP querying and treating performance of the hybrid processor platform on the whole.

Description

technical field [0001] The invention relates to a data warehouse query processing method, in particular to a method for optimizing complex multi-dimensional query processing by using a general-purpose GPU as a connection bitmap storage and processing engine under the mixed architecture of GPU and CPU, and belongs to the technical field of database management. Background technique [0002] At present, microprocessor technology is mainly divided into two development trends: one is multi-core general-purpose processor technology, and the other type is many-core coprocessor technology. The multi-core general-purpose processor is represented by Intel's multi-core processor technology, and its main features are a small number of processing cores and multi-level cache (cache). Many-core coprocessors mainly use NVIDIA's general-purpose GPU (General Purpose Graphics Processing Unit, abbreviated as GPGPU) and Intel's Xeon Phi TM The coprocessor is represented. Judging from current a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 张延松张宇
Owner RENMIN UNIVERSITY OF CHINA
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