Odd-Even Transposition Sort is a parallel sorting algorithm. It is based on the Bubble Sort technique, which compares every 2 consecutive numbers in the array and swap them if first is greater than the second to get an ascending order array. It consists of 2 phases – the odd phase and even phase:
- Odd phase: Every odd indexed element is compared with the next even indexed element(considering 1-based indexing).
- Even phase: Every even indexed element is compared with the next odd indexed element.
This article uses the concept of multi-threading, specifically pthread. In each iteration, every pair of 2 consecutive elements is compared using individual threads executing in parallel as illustrated below.
Examples:
Input: { 2, 1, 4, 9, 5, 3, 6, 10 }
Output: 1, 2, 3, 4, 5, 6, 9, 10
Input: { 11, 19, 4, 20, 1, 22, 25, 8}
Output: 1, 4, 8, 11, 19, 20, 22, 25
Note: Compile the program using following command on your Linux based system.
g++ program_name.cpp -pthread
Below is the implementation of the above topic:
CPP
#include <bits/stdc++.h>
#include <pthread.h>
using namespace std;
#define n 8
int max_threads = (n + 1) / 2;
int a[] = { 2, 1, 4, 9, 5, 3, 6, 10 };
int tmp;
void * compare( void * arg)
{
int index = tmp;
tmp = tmp + 2;
if ((index + 1 < n) && (a[index] > a[index + 1])) {
swap(a[index], a[index + 1]);
}
}
void oddEven(pthread_t threads[])
{
int i, j;
for (i = 1; i <= n; i++) {
if (i % 2 == 1) {
tmp = 0;
for (j = 0; j < max_threads; j++)
pthread_create(&threads[j], NULL, compare, NULL);
for (j = 0; j < max_threads; j++)
pthread_join(threads[j], NULL);
}
else {
tmp = 1;
for (j = 0; j < max_threads - 1; j++)
pthread_create(&threads[j], NULL, compare, NULL);
for (j = 0; j < max_threads - 1; j++)
pthread_join(threads[j], NULL);
}
}
}
void printArray()
{
int i;
for (i = 0; i < n; i++)
cout << a[i] << " " ;
cout << endl;
}
int main()
{
pthread_t threads[max_threads];
cout << "Given array is: " ;
printArray();
oddEven(threads);
cout << "\nSorted array is: " ;
printArray();
return 0;
}
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Python3
from threading import Thread
N = 8
MAX_THREAD = int ((N + 1 ) / 2 )
arr = [ 2 , 1 , 4 , 9 , 5 , 3 , 6 , 10 ]
tmp = 0
def compare():
global tmp
index = tmp
tmp = tmp + 2
if index + 1 < N and arr[index] > arr[index + 1 ]:
arr[index], arr[index + 1 ] = arr[index + 1 ], arr[index]
def createThreads():
threads = list ( range (MAX_THREAD))
for index in range (MAX_THREAD):
threads[index] = Thread(target = compare)
threads[index].start()
for index in range (MAX_THREAD):
threads[index].join()
def oddEven():
global tmp
for i in range ( 1 , N + 1 ):
if i % 2 :
tmp = 0
createThreads()
else :
tmp = 1
createThreads()
if __name__ = = "__main__" :
print ( "Given array is : %s" % arr)
oddEven()
print ( "Sorted array is : %s" % arr)
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Output:
Given array is: 2 1 4 9 5 3 6 10
Sorted array is: 1 2 3 4 5 6 9 10
Time complexity: The time complexity is reduced to O(N) due to parallel computation using threads. Work complexity: The work complexity of this program is O(N) as N/2 number of threads(resources) are being used to sort the array. So, the work-time complexity of the program is O(N^2).