首页> 外文会议>Frontiers of Massively Parallel Computation, 1990. Proceedings., 3rd Symposium on the >Hash table and sorted array: a case study of multi-entry data structures in massively parallel systems
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Hash table and sorted array: a case study of multi-entry data structures in massively parallel systems

机译:哈希表和排序数组:大规模并行系统中多条目数据结构的案例研究

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The tree, hash table, and sorted array data structures for implementing the primitive operations of a search table are considered. It is argued that the tree structure suffers from the bottleneck problem created by the single entry point, namely, the root, resulting in a linear time complexity. For the hash table and sorted array, the average time complexity for implementing three major operations, namely, insert, delete, and search, is derived. Both analytical and simulation results show that using a sorted array gives a much better performance than using a hash table with linear probing in implementing search table abstraction when the load of the hash table is more than 80%. However, given a hash table having less than 80% load, the average time complexity becomes better than O(log/sup 2/M), i.e. the hash table gives a better performance in search table implementation than the sorted array. Nevertheless, a larger number of processors is required.
机译:考虑了用于实现搜索表原始操作的树,哈希表和排序数组数据结构。有人认为,树结构受单一入口点即根所产生的瓶颈问题的困扰,导致线性时间复杂度。对于哈希表和排序数组,得出实现三个主要操作(即插入,删除和搜索)的平均时间复杂度。分析和仿真结果均表明,当哈希表的负载超过80%时,使用带线性探测的哈希表实现搜索表抽象时,其性能要好得多。然而,给定哈希表具有小于80%的负载,平均时间复杂度变得优于O(log / sup 2 / M),即,哈希表在搜索表实现中的性能要优于排序数组。然而,需要更多的处理器。

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