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Hash table and sorted array: a case study of multi-entry data structures in massively parallel systems

机译:哈希表和排序阵列:大型并行系统中多输入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:考虑用于实现搜索表的原始操作的树,散列表和排序阵列数据结构。有人认为,树结构遭受了单个入口点创建的瓶颈问题,即根,导致线性时间复杂度。对于哈希表和排序阵列,派生了实现三个主要操作,即插入,删除和搜索的平均时间复杂度。分析和仿真结果都表明,使用排序阵列的性能比使用带有线性探测的哈希表在实现哈希表的负载超过80%时实现了线性探测。然而,给定具有小于80%负载的哈希表,平均时间复杂度变得优于O(log / sup 2 / m),即散列表在搜索表执行中提供比排序阵列更好的性能。然而,需要更多的处理器。

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