关键词: 多核中央处理器-图形处理器（CPU-GPU）, 流处理器, 异构编程, 列存储, 改进协调模块分布（ICMD）, 任务动态评估分配

Abstract: GPU and integrated CPU-GPU architecture has powerful parallel processing capability and programmable pipeline, which gradually becomes a hot area of database researches. In order to fully explore the parallel abilities of heterogeneous platform, enhance the performance of the column-storage database query, in this paper, it takes full account of differences of system architecture based on heterogeneous platforms, firstly proposes the improved multidimensional data classification method of data partition strategy ICMD based on improving the multi-dimensional data partitioning method（CMD）, using stream processor to process sub-space join operation in parallel. Secondly, through the implementation of query dynamic load using task allocation model evaluation, it makes the query execution in parallel between multi-core CPU, GPU and other accelerator components. At the same time, it uses on-chip global synchronization and efficient implementation, local memory reuse optimization ICMD connection algorithm. Using SSB benchmark test, the experimental results show that  based on the platform of Intel HD Graphics 4600, ICMD connection query receives 1.35 speedup compared to the CPU version and receives 18% performance improvement compared with Ocelot of GPU query engine.

Key words: multi-core Central Processing Unit-Graphics Processing Unit（CPU-GPU）, stream processor, heterogeneous program, column storage, Improved Coordinate Module Distribution（ICMD）, dynamic evaluation of task allocation