TY - GEN
T1 - Parallelization of Cycle Sort Algorithm
AU - Mathew, Anjali
AU - Rao, Prerana C.
AU - Kini, N. Gopalakrishna
AU - Rao, Ashwath B.
N1 - Publisher Copyright:
© Grenze Scientific Society, 2024.
PY - 2024
Y1 - 2024
N2 - Cycle Sort is a straightforward in-place sorting algorithm that is appropriate for certain use cases where limitations on memory or write costs are the main concern.It does this by minimizing the amount of writes to memory.Cycle Sort has an O(n2) time complexity where n is the number of elements in the array to be sorted in both the worst and average cases.Inefficiency may result from this quadratic complexity, particularly for large datasets.This issue can be overcome by applying parallelization techniques to execute this cycle sort algorithm.In this paper, the parallelized solutions for cycle sort using the Message Passing Interface (MPI) programming and Compute Unified Device Architecture (CUDA) programming models are discussed.The elements are separated into smaller arrays, which are then subjected to the sorting cycles in the proposed methods.Until all of the elements in an array are sorted, cycles are applied to them.The findings emphasize the potential advantages of parallelization in reducing the overall computation time for cycle sorting.The outcome of this shows how scalable the parallelized cycle sort method for sorting huge datasets.
AB - Cycle Sort is a straightforward in-place sorting algorithm that is appropriate for certain use cases where limitations on memory or write costs are the main concern.It does this by minimizing the amount of writes to memory.Cycle Sort has an O(n2) time complexity where n is the number of elements in the array to be sorted in both the worst and average cases.Inefficiency may result from this quadratic complexity, particularly for large datasets.This issue can be overcome by applying parallelization techniques to execute this cycle sort algorithm.In this paper, the parallelized solutions for cycle sort using the Message Passing Interface (MPI) programming and Compute Unified Device Architecture (CUDA) programming models are discussed.The elements are separated into smaller arrays, which are then subjected to the sorting cycles in the proposed methods.Until all of the elements in an array are sorted, cycles are applied to them.The findings emphasize the potential advantages of parallelization in reducing the overall computation time for cycle sorting.The outcome of this shows how scalable the parallelized cycle sort method for sorting huge datasets.
UR - https://www.scopus.com/pages/publications/85209077537
UR - https://www.scopus.com/pages/publications/85209077537#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:85209077537
T3 - 15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024
SP - 6011
EP - 6015
BT - 15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024
A2 - Stephen, Janahanlal
A2 - Sharma, Parveen
A2 - Chaba, Yogesh
A2 - Abraham, K. U.
A2 - Anooj, P.K.
A2 - Mohammad, Noor
A2 - Thomas, Gylson
A2 - Srikiran, Satuluri
PB - Grenze Scientific Society
T2 - 15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024
Y2 - 21 June 2024 through 22 June 2024
ER -