CAJ | 학술논문

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．
위제고완존민감CSB ＋-수색인적조작효솔，재도형처리기（GPU）상연구CSB ＋-수적병행구건화사순성능．통과분석색인수내부절점적매일건여대응협자절점적영사관계，제출료일충일차성병행구건CSB ＋-수소유내부절점건치적무쇄병행산법，이최대병행도래쾌속구건색인수．해산법통과설계GPU평태상지지CSB ＋-수적색인수거임의신축적동태수조래해결GPU상불능동태분배현존공간적문제，통과재색인내부절점적변계증가전충위래감소선정괴적선정분지수，종이제고CSB ＋-수적사순효솔．실험결과표명，문중소제산법적운행시간비기우단개절점화기우수층적병행산법분별제고료31.0화1．4배．
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).In the investigation,first,the mapping relationship between each key in internal nodes and the corresponding leaf node of the index tree is analyzed,a lock-free parallel algorithm that once for all builds the CSB +-tree internal node keys 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 allocation of memory space on GPU,and padding bits are added to the boundary of the internal nodes to reduce the number of branches,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.