Journal ArticleDOI
Parallel merge sort
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A parallel implementation of merge sort on a CREW PRAM that uses n processors and O(logn) time; the constant in the running time is small.Abstract:
We give a parallel implementation of merge sort on a CREW PRAM that uses n processors and $O(\log n)$ time; the constant in the running time is small. We also give a more complex version of the algorithm for the EREW PRAM; it also uses n processors and $O(\log n)$ time. The constant in the running time is still moderate, though not as small.read more
Citations
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Book ChapterDOI
Parallel algorithms for shared-memory machines
TL;DR: In this paper, the authors discuss parallel algorithms for shared-memory machines and discuss the theoretical foundations of parallel algorithms and parallel architectures, and present a theoretical analysis of the appropriate logical organization of a massively parallel computer.
MonographDOI
Introduction to Parallel Computing
TL;DR: In this article, a comprehensive introduction to parallel computing is provided, discussing theoretical issues such as the fundamentals of concurrent processes, models of parallel and distributed computing, and metrics for evaluating and comparing parallel algorithms, as well as practical issues, including methods of designing and implementing shared-and distributed-memory programs, and standards for parallel program implementation.
Book
Vector models for data-parallel computing
TL;DR: A model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based is described, and it is argued that data-parallel models are not only practical and can be applied to a surprisingly wide variety of problems, they are also well suited for very-high-level languages and lead to a concise and clear description of algorithms and their complexity.
Journal ArticleDOI
Scans as primitive parallel operations
TL;DR: A study of the effects of adding two scan primitives as unit-time primitives to PRAM (parallel random access machine) models is presented and it is shown that the primitives improve the asymptotic running time of many algorithms by an O(log n) factor, greatly simplifying the description of many technologies.
Book ChapterDOI
Simple linear work suffix array construction
Juha Kärkkäinen,Peter Sanders +1 more
TL;DR: The skew algorithm for suffix array construction over integer alphabets that can be implemented to run in linear time using integer sorting as its only nontrivial subroutine is introduced.
References
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Proceedings ArticleDOI
Sorting networks and their applications
TL;DR: To achieve high throughput rates today's computers perform several operations simultaneously; not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computing operations are done concurrently.
Journal ArticleDOI
Applying Parallel Computation Algorithms in the Design of Serial Algorithms
TL;DR: It is pointed out that analyses of parallelism in computational problems have practical implications even when multi-processor machines are not available, and a unified framework for cases like this is presented.
Journal ArticleDOI
Sorting in c log n parallel steps
TL;DR: A sorting network withcn logn comparisons where in thei-th step of the algorithm the contents of registersRj, andRk, wherej, k are absolute constants then change their contents or not according to the result of the comparison.
Journal ArticleDOI
Parallelism in Comparison Problems
TL;DR: The worst-case time complexity of algorithms for multiprocessor computers with binary comparisons as the basic operations is investigated and the algorithm for finding the maximum is shown to be optimal for all values of k and n.
Proceedings ArticleDOI
Routing, merging and sorting on parallel models of computation
Allan Borodin,John E. Hopcroft +1 more
TL;DR: It is shown that log log n - log log r is asymptotically optimal for rn processors to merge two sorted lists of n elements and is able to achieve such an efficient sort via Valiant's parallel merging algorithm.