A SIMPLE PARALLEL ALGORITHM FOR THE SINGLE FUNCTION COARSEST PARTITION PROBLEM

1994 ◽  
Vol 04 (04) ◽  
pp. 437-445 ◽  
Author(s):  
CLIVE N. GALLEY ◽  
COSTAS S. ILIOPOULOS
Keyword(s):  
Parallel Algorithm ◽  
Parallel Computation ◽  
Simple Algorithm ◽  
Partition Problem ◽  
Pram Model ◽  
Single Function ◽  
Crcw Pram

This paper shows a simple algorithm for solving the single function coarsest partition problem on the CRCW PRAM model of parallel computation using O(n) processors in O( log n) time with O(n1+ε) space.

AN OPTIMAL RANDOMIZED PARALLEL ALGORITHM FOR THE SINGLE FUNCTION COARSEST PARTITION PROBLEM

1996 ◽  
Vol 06 (02) ◽  
pp. 187-193
Author(s):  
JOSEPH JÁJÁ ◽  
KWAN WOO RYU
Keyword(s):  
Parallel Algorithm ◽  
High Probability ◽  
Rooted Tree ◽  
Partition Problem ◽  
Single Function ◽  
Crew Pram ◽  
Euler Tour ◽  
Crcw Pram

We describe a randomized parallel algorithm to solve the single function coarsest partition problem. The algorithm runs in O( log n) time using O(n) operations with high probability on the Priority CRCW PRAM. The previous best known algorithms run in O( log 2 n) time using O(n log 2 n) operations on the CREW PRAM and O( log n) time using O(n log log n) operations on the Arbitrary CRCW PRAM. The technique presented can be used to generate the Euler tour of a rooted tree optimally from the parent representation.

scholarly journals An Efficient Parallel Algorithm for the Single Function Coarsest Partition Problem on the EREW PRAM

ETRI Journal ◽  
1999 ◽  
Vol 21 (2) ◽  
pp. 22-30
Author(s):  
Kyeoung-Ju Ha Ha ◽  
Kyo-Min Ku Ku ◽  
Hae-Kyeong Park Park ◽  
Young-Kook Kim Kim ◽  
Kwan-Woo Ryu Ryu
Keyword(s):  
Parallel Algorithm ◽  
Partition Problem ◽  
Erew Pram ◽  
Single Function

PARALLEL ALGORITHMS FOR HAMILTONIAN 2-SEPARATOR CHORDAL GRAPHS

2002 ◽  
Vol 12 (01) ◽  
pp. 51-64 ◽  
Author(s):  
B. S. PANDA ◽  
VIJAY NATARAJAN ◽  
SAJAL K. DAS
Keyword(s):  
Parallel Algorithms ◽  
Parallel Algorithm ◽  
Hamiltonian Cycle ◽  
Chordal Graph ◽  
Chordal Graphs ◽  
Pram Model ◽  
Crew Pram ◽  
Crcw Pram

In this paper we propose a parallel algorithm to construct a one-sided monotone polygon from a Hamiltonian 2-separator chordal graph. The algorithm requires O( log n) time and O(n) processors on the CREW PRAM model, where n is the number of vertices and m is the number of edges in the graph. We also propose parallel algorithms to recognize Hamiltonian 2-separator chordal graphs and to construct a Hamiltonian cycle in such a graph. They run in O( log 2 n) time using O(mn) processors on the CRCW PRAM model and O( log 2 n) time using O(m) processors on the CREW PRAM model, respectively.

On the Computing Power of Arrays of Processors with Optical Pipelined Buses

1998 ◽  
Vol 08 (04) ◽  
pp. 503-513
Author(s):  
M. Hamdi ◽  
C. Qiao ◽  
Y. Pan
Keyword(s):  
Parallel Computation ◽  
Computer Systems ◽  
Parallel Computer ◽  
Computing Power ◽  
Time Performance ◽  
Pram Model ◽  
Multiple Processors ◽  
Crcw Pram

This paper examines the computing power of optical parallel computer systems. We consider the proposed Array of Processors with optical Pipelined Buses (APPB) in particular, where processors communicate with each other via a spanning optical bus. APPB allow simultaneous access by multiple processors to the optical bus through message pipelining, thus overcoming the bottlenecks caused by exclusive access when employing electronic buses. We give an overview of this model of parallel computation, and then examine the computing power of APPB by demonstrating its capability to efficiently emulate the CRCW PRAM model. We show that an APPB is almost as powerful as a CRCW PRAM. That is, an APPB can emulate a CRCW PRAM with only a small degradation in time performance.

scholarly journals Length of Maximal Common Subsequences

1992 ◽  
Vol 21 (426) ◽  
Author(s):  
Kim Skak Larsen
Keyword(s):  
Dynamic Programming ◽  
Parallel Algorithm ◽  
Linear Time ◽  
Programming Approach ◽  
Simple Modification ◽  
Dynamic Programming Approach ◽  
Pram Model ◽  
Crew Pram ◽  
The Common ◽  
Crcw Pram

<p>The problem of computing the length of the maximal common subsequences of two strings is quite well examined in the sequential case. There are many variations, but the standard approach is to compute the length in quadratic time using dynamic programming. A linear-time parallel algorithm can be obtained via a simple modification of this strategy by letting a linear number of processors sweep through the table created for the dynamic programming approach.</p><p>However, the contribution of this paper is to show that the problem is in NC. More specifically, we show that the length of the maximal common subsequences of two strings <em>s</em> and <em>t</em> can be computed in time O(log |s| € log |t|) in the CREW PRAM model and in time Theta(min(log |s|, log |t|)) in the COMMON CRCW PRAM model.</p>

AN Ω(log n−k log k) TIME LINEAR COST LOWER BOUND FOR THE k FUNCTIONS COARSEST PARTITION PROBLEM

1996 ◽  
Vol 06 (02) ◽  
pp. 195-202
Author(s):  
CLIVE N. GALLEY
Keyword(s):  
Lower Bound ◽  
Partition Problem ◽  
Model Of Computation ◽  
Pram Model ◽  
Linear Cost ◽  
Time Linear ◽  
Crcw Pram

We consider the k functions coarsest partition problem for a set S, where |S|=n, and k functions from S to S. We present an Ω(log n−k log k) time, linear work, lower bound for this problem on the CRCW PRAM model of computation.

SUB-LOGARITHMIC ALGORITHMS FOR THE LARGEST EMPTY RECTANGLE PROBLEM

1993 ◽  
Vol 03 (01) ◽  
pp. 79-85
Author(s):  
STEPHAN OLARIU ◽  
WENHUI SHEN ◽  
LARRY WILSON
Keyword(s):  
Parallel Algorithms ◽  
Erew Pram ◽  
Pram Model ◽  
The Common ◽  
Crcw Pram ◽  
Natural Way

We show that the Largest Empty Rectangle problem can be solved by reducing it, in a natural way, to the All Nearest Smaller Values problem. We provide two classes of algorithms: the first one assumes that the input points are available sorted by x (resp. y) coordinate. Our algorithm corresponding to this case runs in O(log log n) time using [Formula: see text] processors in the Common-CRCW-PRAM model. For unsorted input, we present algorithms that run in [Formula: see text] time using [Formula: see text] processors in the Common-CRCW-PRAM, or in O( log n) time using [Formula: see text] processors in the EREW-PRAM model. No sub-logarithmic time parallel algorithms have been previously reported for this problem.

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