Performance Analysis of Various Combination Sorting Algotirthms for Large Dataset to fit to a Multi-Core Architecture

A data structure is a specific and systematic way of storing and organizing data in a computer so that it can be accessed and revised efficiently. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data. An algorithm is a finite sequence of steps for solving a problem. All sorting algorithms apply to specific kind of problems. Some sorting algorithms apply to less number of elements, and others for large number of data. Likewise, some sorting algorithm are used for data with duplicate values and some are for floating point numbers. The increasing computation power in modern computers in the form of several cores per processor and more processors, makes it necessary to rethink or to redesign sequential algorithms and data structures. In this paper we introduce 3 new modified algorithms. They are Ins-merge, Quick-merge and Binary Search Tree with duplicate keys (BSTD). The goal of this paper is to develop modified algorithms for sorting on large data and to define an “n” which can be an absolute value or a function of total number of elements in data set and to make it fit into a multi-core processor to improve the computational performance.