R. M. Karp and V. Ramachandran. Parallel algorithms for shared memory machines. Volume A of van Leeuwen [19], 1990. Home/Search Document Not in Database Summary Related Articles Check |
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A Parallel Algorithm For Transitive Closure - Cáceres, Song (Correct)
.... 2, 7, 8, 9, 14, 16, 19] These sequential solutions, usually are based on the use of the adjacency matrix of the digraph, considered as a Boolean matrix or use the adjacency matrix in more directed terms as a problem representation [13] Parallel algorithms for this problem where presented by [10, 12] (PRAM) 11] Arrays and Trees and Meshes of Trees) and [17] Highly Scalable Multiprocessors) We present an algorithm for computing the transitive closure of an acyclic digraph using the BSP CGM Model. Partially supported by FINEP PRONEX SAI Proc. No. 76.97.1022.00. Partially supported ....
....Research Program Proc. No. 68.0037 99 3. Partially supported by the Conselho Nacional de Desenvolvimento Cient ifico e Tecnol ogico, CNPq, and by the Fundac ao de Amparo a Pesquisa do Estado do Rio de Janeiro, FAPERJ, Brazil. 1 2 Coarse Grained Multicomputer (CGM) Model The PRAM model [12] has been extensively utilized to produce important theoretical results on parallel algorithms. However, many of such algorithms could not be employed on real parallel machines. The limitations of the real machines, as compared to the requirements of the PRAM model, are both the number of ....
R. M. Karp and V. Ramachandran, Parallel Algorithms for Shared-Memory Machines, in: J. van Leeuwen, ed., Handbook of Theoretical Computer Science Vol. A, (The MIT Press/Elsevier, 1990) Chapter 17, 869--941.
A Parallel Algorithm for Transitive Closure - Caceres, Song (Correct)
.... 2, 7, 8, 9, 14, 16, 19] These sequential solutions, usually are based on the use of the adjacency matrix of the digraph, considered as a Boolean matrix or use the adjacency matrix in more directed terms as a problem representation [13] Parallel algorithms for this problem where presented by [10, 12] (PRAM) 11] Arrays and Trees and Meshes of Trees) and [17] Highly Scalable Multiprocessors) We present an algorithm for computing the transitive closure of an acyclic digraph using the BSP CGM Model. Partially supported by CNPq and FINEP PRONEX SAI Proc. No. 76.97.1022.00. Partially ....
....Research Program Proc. No. 68.0037 99 3. Partially supported by the Conselho Nacional de Desenvolvimento Cientfico e Tecnologico, CNPq, and by the Fundac ao de Amparo a Pesquisa do Estado do Rio de Janeiro, FAPERJ, Brazil. 2 Coarse Grained Multicomputer (CGM) Model The PRAM model [12] has been extensively utilized to produce important theoretical results on parallel algorithms. However, many of such algorithms could not be employed on real parallel machines. The limitations of the real machines, as compared to the requirements of the PRAM model, are both the number of ....
R. M. Karp and V. Ramachandran, Parallel Algorithms for Shared-Memory Machines, in: J. van Leeuwen, ed., Handbook of Theoretical Computer Science Vol. A, (The MIT Press/Elsevier, 1990) Chapter 17, 869--941.
Finding Strongly Connected Components in Parallel.. - McLendon, III.. (2001) (Correct)
....in more than one SCC. Tarjan s classic serial algorithm for detection of SCCs runs linearly with respect to the number of edges and uses depth rst search [15] However, depth rst search is known to be dicult to parallelize the special case of lexicographical depth rst search is P Complete [11, 14], which in practical terms means it is unlikely that a scalable parallel algorithm exists. There are some parallel algorithms for detecting SCCs that do not rely on depth rst search. 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 (b) a) 16 15 14 13 12 11 10 9 8 7 6 1 2 3 4 ....
R. Karp and V. Ramachandran, Parallel Algorithms for Shared-Memory Machines, Handbook of Theoretical Computer Science - Volume A, ed. J. Van Leeuwen, Elsevier Science Publishers/The MIT Press, Amsterdam, 1990, pp. 869-941.
Executing Multithreaded Programs Efficiently - Blumofe (1995) (12 citations) (Correct)
....performance abstraction based on work and critical path length. The use of work and critical path length to analyze parallel algorithms and model application performance is also not new. Work and critical path have been used in the theory community for years to analyze parallel algorithms [64]. Blelloch [8] has developed a performance model for data parallel computations based on these same two abstract measures. He cites many advantages to such a model over machine based models. Cilk provides a similar performance model for the domain of multithreaded computation. Adaptive ....
Richard M. Karp and Vijaya Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science--- Volume A: Algorithms and Complexity, chapter 17, pages 869--941. MIT Press, Cambridge, Massachusetts, 1990.
Parallel Parsing - de Vreught (1993) (Correct)
....used is Rytter s pebble game. We will discuss this pebble game in full depth when we discuss Rytter s algorithm (chapter 3.2) A third technique that is presumed to be well known is using parallel tree contraction algorithms operating by means of rake operations. We will use the description in [KR90] as the prime example of a parallel tree contraction algorithm (although there the rake operation is called shunt ) Tree Contraction: Number the n leafs from left to right as 1 : n Rake in parallel all odd numbered left leaves Rake in parallel all odd numbered right leaves Shift out ....
R.M. Karp and V. Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, volume A: Algorithms and Complexity, pages 869--941. Elsevier, 1990.
Powerlist: A Structure for Parallel Recursion - Misra (1994) (30 citations) (Correct)
....in [18] This material is based in part upon work supported by the Texas Advanced Research Program under Grant No. 003658 219 and by the National Science Foundation Award CCR 9111912. A notable exception is the recursive description of a prefix sum algorithm in Karp and Ramachandran[12]. A data structure, powerlist, is proposed in this paper that highlights the role of both parallelism and recursion. Many of the known parallel algorithms FFT, Batcher Merge, Prefix Sum, embedding arrays in hypercubes, etc. have surprisingly concise descriptions using powerlists. Simple ....
Richard M. Karp and Vijaya Ramachandran. Parallel algorithms for shared memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science. Elsevier and the MIT Press, 1990.
An Optimal Parallel Algorithm for Formula Evaluation - Buss, Cook, Gupta.. (1990) (28 citations) Self-citation (Ramachandran) (Correct)
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Richard M. Karp and Vijaya Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, pages 869--941. Elsevier, 1990.
Linear Programming with Two Variables per Inequality.. - Lueker, Megiddo.. (1990) (9 citations) Self-citation (Ramachandran) (Correct)
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R. M. Karp and V. Ramachandran, "Parallel algorithms for shared memory machines ", in: Handbook of Theoretical Computer Science,J.van Leeuwen, ed., NorthHolland, 1 988, to appear.
A Randomized Time-Work Optimal Parallel Algorithm for.. - Pettie, Ramachandran (2002) Self-citation (Ramachandran) (Correct)
....tree, optimal algorithm, EREW PRAM AMS subject classifications. 05C85, 68R10, 68Q85 PII. S0097539700371065 1. Introduction. We present a randomized parallel algorithm to find a minimum spanning forest (MSF) in an edge weighted, undirected graph. On an exclusive read exclusive write (EREW) PRAM [KR90] our algorithm runs in expected logarithmic time and linear work in the size of the input; these bounds also hold with high probability in the size of the input. This result is optimal w.r.t. both work and parallel time and is the first provably optimal parallel algorithm for this problem under ....
R. M. Karp and V. Ramachandran, Parallel algorithms for shared-memory machines, in Handbook of Theoretical Computer Science, Vol. A, Elsevier Science, Amsterdam, The Netherlands, 1990, pp. 869--941.
ERCW PRAMs and Optical Communication - MacKenzie, Ramachandran (1996) Self-citation (Ramachandran) (Correct)
....much attention, due in part to a general belief that concurrent writing does not add much power to a model without concurrent reading. We show that this is not always the case by presenting algorithms that solve problems on the ERCW PRAM much faster than they could be solved on the EREW PRAM. See [34] for more details on the different PRAM models. We further motivate the ERCW PRAM by its relation to parallel computers with optical communication networks. Since there is no queue delay in optical communication networks, the ERCW PRAM is a better model for parallel machines with such networks ....
R. M. Karp and V. Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity, chapter 17, pages 869--941. MIT Press/Elsevier, 1990.
Upper Bounds on the Computational Power of an Optical Model of.. - Woods (2005) (Correct)
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R. M. Karp and V. Ramachandran. Parallel algorithms for shared memory machines. Volume A of van Leeuwen [19], 1990.
Lower Bounds on the Computational Power of an Optical Model of .. - Woods, gibson (2005) (Correct)
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R. M. Karp and V. Ramachandran. Parallel algorithms for shared memory machines. Volume A of van Leeuwen [13], 1990. 13
Computational Complexity of an Optical Model of Computation - Woods (2005) (Correct)
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Richard. M. Karp and Vijaya Ramachandran. Parallel algorithms for shared memory machines. Volume A of van Leeuwen [vL90], 1990.
On the Parallel Time Complexity of Undirected Connectivity.. - Chong, Han, Lam (1999) (8 citations) (Correct)
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R.M. Karp and V. Ramachandran, Parallel Algorithms for Shared-Memory Machines, Handbook of Theoretical Computer Science, vol A, J. van Leeuwen Ed., MIT Press, 1990, pp. 869-941.
An Optimal Randomized Logarithmic Time Connectivity Algorithm .. - Halperin, Zwick (1994) (12 citations) (Correct)
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R. M. Karp and V. Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, Volume A, Algorithms and Complexity, chapter 17, pages 869-932. Elsevier and The MIT Press, 1990.
Logic Programs and Connectionist Networks - Hitzler, Hölldobler, Seda (2004) (Correct)
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Richard M. Karp and Vijaya Ramachandran. Parallel algorithms for sharedmemory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, chapter 17, pages 869--941. Elsevier Science Publishers B.V., New York, 1990.
Probabilistic Algorithms for Geometric Elimination - Matera (1999) (1 citation) (Correct)
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R. Karp and V. Ramachandran. Parallel algorithms for shared{memory machines. In Handbook of Theoretical Computer Science, pp. 871-941. Elsevier Science Publishers, 1990.
The Design and Analysis of Bulk-Synchronous Parallel Algorithms - Tiskin (1998) (7 citations) (Correct)
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R. M. Karp and V. Ramachandran. Parallel algorithms for shared memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, chapter 17, pages 869--941. Elsevier, 1990.
The Design and Analysis of Bulk-Synchronous Parallel Algorithms - Tiskin (1998) (7 citations) (Correct)
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R. M. Karp and V. Ramachandran. Parallel algorithms for shared memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, chapter 17, pages 869--941. Elsevier, 1990.
Thinking in Parallel: Some Basic Data-Parallel Algorithms and.. - Vishkin (2002) (1 citation) (Correct)
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R.M. Karp and V. Ramachandran. Parallel algorithms for shared-memory machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity, pages 869--942. MIT Press, 1990.
Graph Coloring on Coarse Grained Multicomputers - Gebremedhin, Lassous.. (2003) (1 citation) (Correct)
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R. Karp and V. Ramachandran. Parallel algorithms for shared-memory machines. In Handbook of Theoretical Computer Science Volume A: Algorithms and Complexity, pages 869--942. Elsevier, 1990.
PRO: a Model for Parallel Resource-Optimal Computation - Gebremedhin, Lassous.. (Correct)
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R. M. Karp and V. Ramachandran. Parallel Algorithms for SharedMemory Machines. In Jan van Leeuwen, editor, Handbook of Theoretical Computer Science, volume A, Algorithms and Complexity, pages 869-- 941. Elsevier Science Publishers B.V., Amsterdam, 1990.
PRO: a Model for Parallel Resource-Optimal Computation - Gebremedhin, Lassous.. (2001) (Correct)
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R. M. Karp and V. Ramachandran. Parallel Algorithms for Shared-Memory Machines. In Jan van Leeuwen, editor, Handbook of Theoretical Computer Science, volume A, Algorithms and Complexity, pages 869--941. Elsevier Science Publishers B.V., Amsterdam, 1990.
PRO: a Model for Parallel Resource-Optimal Computation - Gebremedhin, Guerin, Gustedt (Correct)
No context found.
R. M. Karp and V. Ramachandran. Parallel Algorithms for Shared-Memory Machines. In J. van Leeuwen, editor, Handbook of Theoretical Computer Science, volume A, Algorithms and Complexity, pages 869--941. Elsevier Science Publishers B.V., Amsterdam, 1990.
Descriptive Simplicity in Parallel Computing - Marr (1997) (Correct)
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Richard M Karp and Vijaya Ramachandran. Parallel algorithms for shared-memory machines. In J van Leeuwen, editor, Handbook of Theoretical Computer Science, chapter 17, pages 871--941. Elsevier Science Publishers B.V., 1990.
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