A taxonomy of parallel sorting
ACM Computing Surveys (CSUR)
An introduction to programming in SIMULA
An introduction to programming in SIMULA
Designing efficient algorithms for parallel computers
Designing efficient algorithms for parallel computers
DEMOS: a system for discrete event modelling on Simula
DEMOS: a system for discrete event modelling on Simula
Efficient parallel algorithms
Programming pearls
Sorting in c log n parallel steps
Combinatorica
SIAM Journal on Computing
The design and analysis of parallel algorithms
The design and analysis of parallel algorithms
Parallel Sorting Algorithms
Data Structures and Algorithms
Data Structures and Algorithms
Parallelism in random access machines
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
Tight bounds on the complexity of parallel sorting
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Improved Sorting Networks with O(log n) Depth
Improved Sorting Networks with O(log n) Depth
The complexity of parallel computations
The complexity of parallel computations
Simula Begin
Radix sort for vector multiprocessors
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
GPU-ABiSort: optimal parallel sorting on stream architectures
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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When looking for new and faster parallel sorting algorithms for use in massively parallel systems it is tempting to investigate promising alternatives from the large body of research done on parallel sorting in the field of theoretical computer science. Such “theoretical” algorithms are mainly described for the PRAM (Parallel Random Access Machine) model of computation [13,26]. This paper shows how this kind of investigation can be done on a simple but versatile environment for programming and measuring of PRAM algorithms [19,20]. The practical value of Cole's Parallel Merge Sort algorithm [10,11] have been investigated by comparing it with Batcher's bitonic sorting [5]. The &Ogr;(log n) time consumption of Cole's algorithm implies that it must be faster than bitonic sorting which is &Ogr;(log2 n) time-if n is large enough. However, we have found that bitonic sorting is faster as long as n is less than 1.2 x 1021, i.e. more than 1 Giga Tera items!. Consequently, Cole's logarithmic time algorithm is not fast in practice.