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I wanna implement a fast algorithm for a homework, but using parallel processing for this task. I heard that the parallel version of Quicksort is the best choice, but I'm not sure of this... maybe Heapsort is a good idea. Which algorithm do you think is the best one for a parallelized environment, and why?
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Like merge sort, quicksort can also be easily parallelized due to its divide-and-conquer nature. Individual in-place partition operations are difficult to parallelize, but once divided, different sections of the list can be sorted in parallel.
Quicksort. Quicksort is one of the most efficient sorting algorithms, and this makes of it one of the most used as well. The first thing to do is to select a pivot number, this number will separate the data, on its left are the numbers smaller than it and the greater numbers on the right.
What is the easiest sorting algorithm? Bubble sort is widely recognized as the simplest sorting algorithm out there. Its basic idea is to scan through an entire array and compare adjacent elements and swap them (if necessary) until the list is sorted.
Insertion sort runs much more efficiently if the array is already sorted or "close to sorted." Selection sort always performs O(n) swaps, while insertion sort performs O(n2) swaps in the average and worst case. Selection sort is preferable if writing to memory is significantly more expensive than reading.
Quick sort can split the unsorted list into two halves, but unfortunately, the halves aren't guaranteed to be anywhere near even. So one machine (or half of a cluster of machines) could get 20 entries, and the other half could get 20 billion.
I can't think of a good way to make heapsort work in parallel. It can be done, but man, that feels really counterintuitive.
Merge sort is the one I think you want.
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