A Parallel Random Access Machine (PRAM) Model for English Language Recognizer (PRAM-ELR)

Two parallel geometric algorithms based on the idea of point domination are presented. The first algorithm solves the d-dimensional isothetic rectangles intersection counting problem of input size N/2d, where d>1 and N is a multiple of 2d, in O( log d−1 N) time and O(N log N) space. The second algorithm solves the direct dominance reporting problem for a set of N points in the plane in O( log N+J) time and O(N log N) space, where J denotes the maximum of the number of direct dominances reported by any single point in the set. Both algorithms make use of the EREW PRAM (Exclusive Read Exclusive Write Parallel Random Access Machine) consisting of O(N) processors as the computational model.

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A Simple Optimal Parallel Algorithm for Reporting Paths in a Tree

Parallel Processing Letters ◽

10.1142/s0129626497000036 ◽

1997 ◽

Vol 07 (01) ◽

pp. 3-11 ◽

Cited By ~ 1

Author(s):

Andrzej Lingas ◽

Anil Maheshwari

Keyword(s):

Parallel Algorithm ◽

Random Access ◽

Input Tree ◽

Single Pair ◽

Random Access Machine ◽

Erew Pram ◽

Parallel Random Access Machine ◽

Path Queries

We present optimal parallel solutions to reporting paths between pairs of nodes in an n-node tree. Our algorithms are deterministic and designed to run on an exclusive read exclusive write parallel random-access machine (EREW PRAM). In particular, we provide a simple optimal parallel algorithm for preprocessing the input tree such that the path queries can be answered efficiently. Our algorithm for preprocessing runs in O( log n) time using O(n/ log n) processors. Using the preprocessing, we can report paths between k node pairs in O( log n + log k) time using O(k + (n + S)/ log n) processors on an EREW PRAM, where S is the size of the output. In particular, we can report the path between a single pair of distinct nodes in O( log n) time using O(L/ log n) processors, where L denotes the length of the path.

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Transforming Comparison Model Lower Bounds to the PRAM

BRICS Report Series ◽

10.7146/brics.v2i10.19513 ◽

1995 ◽

Vol 2 (10) ◽

Author(s):

Dany Breslauer ◽

Devdatt P. Dubhashi

Keyword(s):

Decision Tree ◽

Lower Bounds ◽

Random Access ◽

Decision Tree Model ◽

Tree Model ◽

Machine Model ◽

Comparison Model ◽

Random Access Machine ◽

Input Domain ◽

Parallel Random Access Machine

This note provides general transformations of lower bounds in Valiant's parallel comparison decision tree model to lower bounds in the priority concurrent-read concurrent-write parallel-random-access-machine model. The proofs rely on standard Ramsey-theoretic arguments that simplify the structure of the computation by restricting the input domain. The transformation of comparison model lower bounds, which are usually easier to obtain, to the parallel-random-access-machine, unifies some known lower bounds and gives new lower bounds for several problems.

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The bulk-synchronous parallel random access machine

Theoretical Computer Science ◽

10.1016/s0304-3975(97)00197-7 ◽

1998 ◽

Vol 196 (1-2) ◽

pp. 109-130 ◽

Cited By ~ 18

Author(s):

Alexandre Tiskin

Keyword(s):

Random Access ◽

Bulk Synchronous Parallel ◽

Random Access Machine ◽

Parallel Random Access Machine

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Total Eclipse - an Efficient Architectural Realization of the Parallel Random Access Machine

Parallel and Distributed Computing ◽

10.5772/9446 ◽

2010 ◽

Cited By ~ 11

Author(s):

Martti Forsell

Keyword(s):

Random Access ◽

Random Access Machine ◽

Total Eclipse ◽

Parallel Random Access Machine

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PARALLEL RECOGNITION OF HIGH DIMENSIONAL IMAGES

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001492000175 ◽

1992 ◽

Vol 06 (02n03) ◽

pp. 285-291 ◽

Cited By ~ 1

Author(s):

M. NIVAT ◽

A. SAOUDI

Keyword(s):

Time Complexity ◽

Random Access ◽

Space Complexity ◽

Recognition Problem ◽

High Dimensional ◽

Context Free Grammar ◽

Random Access Machine ◽

Parallel Random Access Machine ◽

Context Free ◽

Context Free Grammars

We investigate the complexity of the recognition of images generated by a class of context-free image grammars. We show that the sequential time complexity of the recognition of an n × n image as generated by a context-free grammar is O(nM(n)), where M(n) is the time to multiply two boolean n × n matrices. The space complexity of this recognition is O(n3). Using a parallel random access machine (i.e. PRAM), the recognition can be done in O( log 2(n)) time with n7 processors or in O(n log 2(n)) time with n6 processors. We also introduce high dimensional context-free grammars and prove that their recognition problem is polylogarithmic.

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ON THE PERFORMANCE AND COST OF SOME PRAM MODELS ON CMP HARDWARE

International Journal of Foundations of Computer Science ◽

10.1142/s0129054110007325 ◽

2010 ◽

Vol 21 (03) ◽

pp. 387-404 ◽

Cited By ~ 4

Author(s):

MARTTI FORSELL

Keyword(s):

Random Access ◽

Chip Multiprocessor ◽

Pram Model ◽

Vlsi Technology ◽

Cost Efficient ◽

Performance Area ◽

And Performance ◽

On Chip ◽

Parallel Random Access Machine ◽

The Cost

The Parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for indirect on-chip implementation, but there are different variants of the PRAM model that provide different performance, area and power figures and it is not known how their implementations compare to each others. In this paper we measure the performance and estimate the cost of practical implementations of four PRAM models including EREW, Limited Arbitrary CRCW, Full Arbitrary CRCW, Full Arbitrary Multioperation CRCW on our Eclipse chip multiprocessor framework. Interestingly, the most powerful model shows the lowest simulation cost and highest performance/area and performance/power figures.

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