为提高缓存敏感 CSB⁺- 树索引的操作效率，在图形处理器( GPU) 上研究 CSB⁺-树的并行构建和查询性能．通过分析索引树内部节点的每一键与对应叶子节点的映射关系，提出了一种一次性并行构建 CSB⁺- 树所有内部节点键值的无锁并行算法，以最大并行度来快速构建索引树．该算法通过设计 GPU 平台上支持 CSB⁺- 树的索引数据任意伸缩的动态数组来解决 GPU 上不能动态分配显存空间的问题，通过在索引内部节点的边界增加填充位来减少线程块的线程分支数，从而提高 CSB⁺- 树的查询效率．实验结果表明，文中所提算法的运行时间比基于单个节点和基于树层的并行算法分别提高了 31. 0 和 1．4 倍．

In order to improve the operation efficiency of cache sensitive B⁺- tree (CSB⁺- tree) indexing,this pa-per deals with the parallel construction and query performance of CSB⁺- tree on graphic processing unit (GPU).Inthe investigation,first,the mapping relationship between each key in internal nodes and the corresponding leafnode of the index tree is analyzed, a lock- free parallel algorithm that once for all builds the CSB⁺- tree internal nodekeys is proposed,and the index tree is constructed at the maximum parallel speed.Moreover, dynamic arrays su-pporting the arbitrary expansion of CSB⁺- tree index data on GPU are designed to implement the dynamic allocationof memory space on GPU,and padding bits are added to the boundary of the internal nodes to reduce the number ofbranches,thus improving the query efficiency of CSB⁺- tree.Experimental results indicate that the proposed algo-rithm is 31. 0 and 1.4 times faster respectively than the parallel algorithms based on single node and tree layer.