Accelerating Large-Scale Sorting through Parallel Algorithms

This study explores the application of parallel algorithms to enhance large-scale sorting, focusing on the QuickSort method. Implemented in both sequential and parallel forms, the paper provides a detailed comparison of their performance. This study investigates the efficacy of both techniques through the lens of array generation and pivot selection to manage datasets of varying sizes. This study meticulously documents the performance metrics, recording 16,499.2 milliseconds for the serial implementation and 16,339 milliseconds for the parallel implementation when sorting an array by using C++ chrono library. These results suggest that while the performance gains of the parallel approach over its serial counterpart are not immediately pronounced for smaller datasets, the benefits are expected to be more substantial as the dataset size increases.

快速外分类算法设计与分析

§1 引言数据库文件的分类是数据处理的重要课题之一,它直接影响数据库的检索效率。目前外分类算法中多数采用分类归并方法[1][2],分类归并过程一般先逐段执行内分类,每次读入内存缓冲区所能容纳的数据,选择一内分类算法将数据整理成有序串,并根据归并的散布算法输出这些有序串,然后数据在内外存间进行归并,以形成一个最终的有序串。