#Sequential program faster than parallel how to#
#Sequential program faster than parallel code#

This way, in the next step, if swaps occur, then we continue inside the loop, otherwise, we break out of it. Then we set Sorted equal to 1 to imply that no swaps occurred and the list is already sorted. If the starting condition is Sorted = 0, this implies that the list is not yet sorted. Using a while loop, we compare all elements in the list as pairs and sort them in phases.Then create a variable to store the length of the list, so that we can traverse and compare all elements in the list in pairs. If no swaps occur in either phase, it means the list is already sorted. This way, we can sort the list and stop the algorithm if no swaps occur. Create a variable called Sorted to keep track of whether swaps occur or not.To implement a parallel version of bubble sort, follow the steps mentioned below. In the case of multi-core processors, both phases can occur simultaneously, which is known as parallel implementation. The process of parallel bubble sort is shown below. When comparing, just like in normal bubble sort, we swap the elements, if the initial element is greater than the next element in comparison.īoth phases occur one after the other and the algorithm stops once no swap occurs in both odd and even phase. In the even phase, we compare index 1 element with index 2 element, index 3 element with index 4 element, and so on, with our last comparison being element at third last index and element at second last index. When it is the odd phase, we compare the element at index 0 with the element at index 1, the element at index 2 with the element at index 3, and so on. We divide the sorting process into two phases- odd phase and even phase. We compare all pairs of elements in the list/array side by side (parallel). In Parallel Bubble Sort, we divide sorting of the unsorted into two phases- odd and even. In parallel sorting, we transform the already existing traditional sorting algorithms in a way such that during execution, instead of sequential execution of algorithm’s instructions. We can also design our algorithms in such a way that the parts of the program run sequentially. This way, even though the programs are sequential, we can implement some degree of parallelism. The hardware and the system are designed in such a way so that the data generated, and the previous, current, and future instructions don’t interrupt each other. Modern-day processors can handle multiple instructions and the data generated from them at the same time. In addition, even sequential programs involve some degree of parallelism. We can solve this problem using multi-core computers. Additionally, the capacity of today’s modern processors that run these sequential programs is limited. Therefore, the degree of parallelism depends on the program and its requirements.

However, some parts of the program may still require other parts of the program to run first.

#Sequential program faster than parallel code#

For example, if there are parts of code that can be implemented independently and executed irrespective of any order, then we can execute at the same time.

Implementation of parallelism depends on some factors. The main benefit of this is faster computation. The concept of parallelism involves executing a set of instructions/code simultaneously instead of line by line sequentially (the traditional way the code is executed in most machines and computer programming generally). Parallel bubble sort is a parallel implementation of the classic Bubble sort algorithm.

Time and Space complexity of Bubble Sort.

Comparison of 3 Bubble Sort implementations.

Alternate Parallel bubble sort using threads (with faster runtime).

We have presented two approaches: one is slower than the sequential approach but the other approach is significantly faster than all other approaches for large input.

#Sequential program faster than parallel how to#

In this article, we have explored how to implement Bubble Sort in parallel on multiple threads / cores.