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About 3,727 papers for “parallel sorting”

Parallel Multidimensional Lookahead Sorting Algorithm

Fayez Gebali, Mohamed Taher, A. Zaki et al. · IEEE Access · 2019

This paper presents a new parallel structured lookahead multidimensional sorting algorithm. Our algorithm can be based on any sequential sorting algorithm. The amount of parallelism can be controlled using several parameters such as the number of threads, word size, memory/processor communication overhead, and the dimension of the algorithm. The proposed technique is ideally suited for general purpose graphic processing units and shared-memory massively parallel processor systems. It ensures that data being processed exhibits temporal and spatial locality to maximize the utilization of processor cache. The algorithm achieves a speedup even when a single processor is used. A lookahead algorithm is also proposed to achieve even higher speedup. The performance of the proposed algorithm is verified numerically and experimentally.

Cited by 7Open access

Doubly Logarithmic Time Parallel Sorting

R. Sarnath · 2007

Recently, attempts have been made to separate the problem of parallel sorting from that of list ranking, in order to get around the well known\\Omega\\Gamma/33 n= log log n) lower bound. These approaches have been of two kinds - chain sorting and padded sorting. Here we present nearly optimal, comparison based padded sorting algorithms that run in average case time O( 1 ffl 2 + 1 ffl log log n) using n 1+ffl processors, and O(n 1+ffl ) space, on an Common CRCW PRAM.From these results, algorithms for chain sorting within the same time and processor bounds can be easily obtained. Using a similar approach, we also give an O(1) average case time, comparison based algorithm for finding the largest of n items using a linear number of processors. The algorithm for finding the maximum, runs on a Common CRCW PRAM using only n 3=4 cells of shared memory. Finally, we obtain randomised algorithms for these problems that run on Common/Tolerant CRCW PRAMs, and also satisfy the above...

Cited by 0

The complexity of parallel sorting

Friedhelm Meyer auf der Heide, Avi Wigderson · 1985

We consider PRAM's with arbitrary computational power for individual processors, infinitely large shared memory and "priority" writeconflict resolution. The main result is that sorting n integers with n processors requires Ω(√log n) steps in this strong model. We also show that computing any symmetric polynomial (e.g. the sum or product) of n integers requires exactly log2n steps, for any finite number of processors.

Cited by 27

Improved sorting algorithms for parallel computers

Arvin Park, K. Balasubramanian · 1987

We make observations that improve processor utilization and decrease communication overhead for several parallel sorting algorithms. These lead to constant factor improvements on the best previous parallel sorting bounds for both mesh-connected and linearly connected parallel architectures [2,12] (Previous bounds were within a constant factor of optimal.). These improved bounds are achieved using fewer processors with greater processor utilization.

Cited by 4

A Heapify Based Parallel Sorting Algorithm

Mwaffaq A. Abu Al hija, Arwa Zabian, Sami Qawasmeh et al. · Journal of Computer Science · 2008

Quick sort is a sorting algorithm whose worst case running time is (n 2 ) on an input array of n numbers. It is the best practical for sorting because it has the advantage of sorting in place. Problem statement: Behavior of quick sort is complex, we proposed in-place 2m threads parallel heap sort algorithm which had advantage in sorting in place and had better performance than classical sequential quick sort in running time. Approach: The algorithm consisted of several stages, in first stage; it splits input data into two partitions, next stages it did the same partitioning for prior stage which had been spitted until 2 m partitions was reached equal to the number of available processors, finally it used heap sort to sort respectively ordered of non internally sorted partitions in parallel. Results: Results showed the speed of algorithm about double speed of classical Quick sort for a large input size. The number of comparisons needed was reduced significantly. Conclusion: In this study we had been proposed a sorting algorithm that uses less number of comparisons with respect to original quick sort that in turn requires less running time to sort the same input data.

Cited by 5Open access

Parallel Sorting on the Biswapped Network

Wenhong Wei, Wenjun Xiao, Zhen Zhang · 2008

Biswapped network (BSN) is a recently proposed network model of parallel computing, which is built of 2n copies of an n-node basic network, and its basic network may be hypercube, mesh and other networks, hence we can construct BSN-Hypercube and BSN-Mesh by using hypercube and mesh as basic network. BSN uses a simple rule for connectivity to ensure its regularity and some topological properties of BSN have been investigated. In this paper, we present sorting algorithm on the n processors BSN whose basic network has Hamiltonian path, and if the basic network of BSN is mesh, sorting n unordered elements will complete in time (2n)^1(1/2)+O(n^(3/4)).

Cited by 2

Parallel Algorithms For Merging And Sorting

Deo, Narsingh, Sarkar, Dilip · Journal of International Crisis and Risk Communication Research · 1991

We present an O(log(min(m,n,j))-time sequential algorithm to select the jth-smallest element of an array resulting from the merging of two sorted arrays A and B of sizes m and n. This algorithm is then used to design two parallel algorithms to partition A and B into p subarrays of size O( (m + n) p) in O( N p + log N) and O( N p + log p log N) times on crew pram and erew pram models with p processors, where N = m + n. A third parallel algorithm has been presented that partitions A and B in O( N p + log p log N) time into p pairs of subarrays of size O( N p) on erew pram with p processors without using any selection algorithm. Finally, these partitioning algorithms are used to obtain optimal parallel merging and sorting algorithms on crew prams and erew prams. © 1991.

Cited by 0Open access

Large and Parallel Human Sorting Networks

Stefan Szeider · Lecture notes in computer science · 2024

Abstract This paper presents two innovative extensions of the classic Human Sorting Network (HSN) activity from the CS Unplugged program. First, we describe the implementation of a large-scale HSN with 50 input nodes, realized with high school students in Vienna, Austria. We detail the logistical challenges and solutions for creating an HSN of this magnitude, including location selection, network layout, and participant coordination. Second, we report on using parallel 6-input HSNs, which introduce a competitive element and enhance engagement. This parallel setup allows for races between teams and can be adapted for various age groups and knowledge levels. Both extensions aim to increase the educational impact and enjoyment of the HSN activity. We provide comprehensive insights into our experiences, enabling other educators and researchers to replicate or further develop these HSN variants.

Cited by 0Open access

Optimal Deterministic Sorting on Parallel Disks

Mark H. Nodine, Jeffrey Scott Vitter · 1992

We present a load balancing technique that leads to an optimal deterministic algorithm called Balance Sort for external sorting on multiple disks. Our measure of performance is the number of input/output (I/O) operations. In each I/O, each of the D disks can simultaneously transfer a block of data. Our algorithm improves upon the randomized optimal algorithm of Vitter and Shriver as well as the (non-optimal) commonly-used technique of disk striping. It also improves upon our earlier mergebased sorting algorithm in that it has smaller constants hidden in the big-oh notation, and it is possible to implement using only striped writes (but independent reads). In a companion paper, we show how to modify the algorithm to achieve optimal CPU time, even on parallel processors and parallel memory hierarchies.

Cited by 11

Algorithm-Based Fault-Tolerant Parallel Sorting

Edson Tavares de Camargo, Elias P. Duarte · International Journal of Critical Computer-Based Systems · 2023

High performance computing (HPC) systems often require substantial resources, and can take up to several hours or days to execute. Upon a failure, it is important to loose as little computation as possible. In this work we present an algorithm-based fault tolerance (ABFT) strategy for hypercube-based parallel algorithms. The strategy assumes the virtual VCube topology, which has several logarithmic properties that are preserved even as nodes fail. The strategy guarantees that the algorithm does not halt even after up to (N - 1) nodes crash, in a system of N nodes. We use parallel sorting as a case study, describing how to make a fault-tolerant version of three parallel sorting algorithms: HyperQuickSort, QuickMerge and Bitonic Sort. The algorithms were implemented in MPI using ULMF to handle faults. Experimental results are presented showing the performance and robustness of the solution for sorting up to a billion integers in scenarios with faults.

Cited by 0

Parallel Algorithms For Merging And Sorting

Journal of International Crisis and Risk Communication Research · 1991

We present an O(log(min(m,n,j))-time sequential algorithm to select the jth-smallest element of an array resulting from the merging of two sorted arrays A and B of sizes m and n. This algorithm is then used to design two parallel algorithms to partition A and B into p subarrays of size O((m + n)/p) in O(N / p + log N) and O(N / p + log p log N) times on CREW PRAM AND EREW PRAM models with p processors, where N = m + n. A third parallel algorithm has been presented that partitions A and B in O(N / p + log p log N) time into p pairs of subarrays of size O(N / p) on EREW PRAM with p processors without using any selection algorithm. Finally, these partitioning algorithms are used to obtain optimal parallel merging and sorting algorithms on CREW PRAMS and EREW PRAMS.

Cited by 0Open access

Parallel Algorithm For Sorting Animal Pedigrees

Maciej Gierdziewicz · SHILAP Revista de lepidopterología · 2009

In many analyses of animal genotype with the methods of quantitative genetics there is a needto account for relationships among individuals. Incorrectly calculated relationship coefficientsmay lead to biased estimates. The number of software packages exist which deal with thatproblem; however, in many of them it is assumed that pedigrees of the individuals are sortedchronologically, but in real data sets – containing information on traits and pedigrees – birthdates are often missing. In extreme cases, when (almost) no birth dates are present, theordering must be made by comparing – at least once – each pair of individuals separately,since it is not sufficient to compare adjacent elements in order to check whether the dataset is sorted. Two versions of parallel computer programs were compared, with constant orvariable distance between elements of compared pairs. The results indicate that the secondalgorithm is more efficient.

Cited by 0Open access