A parallel algorithm for mapping a special class of task graphs onto linear array multiprocessors

1994 ◽  
Author(s):  
Sibabrata Ray ◽  
Hong Jiang ◽  
Jitender S. Deogun
Keyword(s):  
Parallel Algorithm ◽  
Special Class ◽  
Linear Array ◽  
Task Graphs

A PARALLEL ALGORITHM TO GENERATE N-ARY REFLECTED GRAY CODES IN A LINEAR ARRAY WITH RECONFIGURABLE BUS SYSTEM

1993 ◽  
Vol 03 (02) ◽  
pp. 157-164 ◽  
Author(s):  
P. THANGAVEL ◽  
V.P. MUTHUSWAMY
Keyword(s):  
Parallel Algorithm ◽  
Linear Array ◽  
Constant Time ◽  
Processor Array ◽  
Gray Codes ◽  
System A ◽  
Processor Arrays ◽  
Bus System

A simple parallel algorithm for generating N-ary reflected Gray codes is presented. The algorithm is derived from the pattern of N-ary reflected Gray codes. The algorithm runs on a linear processor array with a reconfigurable bus system. A reconfigurable bus system is a bus system whose configuration can be dynamically changed. Recently processor arrays with reconfigurable bus systems were used to solve many problems in constant time. There already exists experimental reconfigurable chips.

A CONSTANT TIME ALGORITHM FOR REDUNDANCY ELIMINATION IN TASK GRAPHS ON PROCESSOR ARRAYS WITH RECONFIGURABLE BUS SYSTEMS

1993 ◽  
Vol 03 (02) ◽  
pp. 171-177 ◽  
Author(s):  
B. PRADEEP ◽  
C. SIVA RAM MURTHY
Keyword(s):  
Parallel Algorithm ◽  
Time Algorithm ◽  
Constant Time ◽  
Redundancy Elimination ◽  
Task Graphs ◽  
Processor Arrays ◽  
Precedence Graph ◽  
Practical Tool ◽  
Algorithm Parallelization

The task or precedence graph formalism is a practical tool to study algorithm parallelization. Redundancy in such task graphs gives rise to numerous avoidable inter-task dependencies which invariably complicates the process of parallelization. In this paper we present an O(1) time algorithm for the elimination of redundancy in such graphs on Processor Arrays with Reconfigurable Bus Systemusing O(n4) processors, The previous parallel algorithm available in the literature for redundancy elimination in task graphs takes O(n2) time using O(n) processors.

TWO ALGORITHMS FOR COMPUTING THE EUCLIDEAN DISTANCE TRANSFORM

2001 ◽  
Vol 01 (04) ◽  
pp. 635-645 ◽  
Author(s):  
MARINA L. GAVRILOVA ◽  
MUHAMMAD H. ALSUWAIYEL
Keyword(s):  
Parallel Algorithm ◽  
Euclidean Distance ◽  
Linear Array ◽  
Linear Time ◽  
Sequential Algorithm ◽  
Distance Transform ◽  
Optimal Algorithms ◽  
Euclidean Metric ◽  
Input Size ◽  
Feature Transform

Given an n × n binary image of white and black pixels, we present two optimal algorithms for computing the distance transform and the nearest feature transform using the Euclidean metric. The first algorithm is a fast sequential algorithm that runs in linear time in the input size. The second is a parallel algorithm that runs in O(n2/p) time on a linear array of p processors, p, 1 ≤ p ≤ n.

GENERATING n-ARY REFLECTED GRAY CODES ON A LINEAR ARRAY OF PROCESSORS

1996 ◽  
Vol 06 (01) ◽  
pp. 27-34 ◽  
Author(s):  
IVAN STOJMENOVIC
Keyword(s):  
Parallel Algorithm ◽  
Arbitrary Number ◽  
Linear Array ◽  
Gray Code ◽  
Gray Codes ◽  
Model Of Computation ◽  
Constant Size

We present a cost-optimal parallel algorithm for generating n-ary reflected Gray codes, i.e. variations of m elements out of {0, 1,…, n–1} in a Gray code order. It uses a linear array of m processors, each having constant size memory and each being responsible for producing one part of a given variation. The algorithm is simple and uses a weaker model of computation than a recently published algorithm. In addition, it can be made adaptive (i.e. to run on a linear array with an arbitrary number of processors) and can be generalized to produce variations out of an arbitrary set of elements.

A One-Phase Parallel Algorithm for the Sequence Alignment Problem

1998 ◽  
Vol 08 (04) ◽  
pp. 515-526 ◽  
Author(s):  
Thierry Lecroq ◽  
Jean-Frederic Myoupo ◽  
David Seme
Keyword(s):  
Parallel Algorithm ◽  
Sequence Alignment ◽  
Edit Distance ◽  
Linear Array ◽  
Systolic Algorithm ◽  
Alignment Problem

This paper introduces a new linear systolic algorithm [10] for the sequence alignment problem [18]. It is made up of min(n, m) processors and computes the edit distance and the sequence alignment of two sequences Target and Source in time min(n, m) + 2.max(n, m), where n and m denote the lengths of Target and Source respectively. Its characteristics make it faster and more efficient than the previous linear array algorithm for the alignment search.

A SIMPLE OPTIMAL SYSTOLIC ALGORITHM FOR GENERATING PERMUTATIONS

1992 ◽  
Vol 02 (02n03) ◽  
pp. 231-239 ◽  
Author(s):  
SELIM G. AKL ◽  
IVAN STOJMENOVIĆ
Keyword(s):  
Parallel Algorithm ◽  
Linear Array ◽  
Constant Delay ◽  
Constant Size ◽  
Time Solution ◽  
Systolic Algorithm

We describe a simple parallel algorithm for generating all permutations of n elements. The algorithm is designed to be executed on a linear array of n processors, each having constant size memory and each being responsible for producing one element of a given permutation. There is a constant delay per permutation, leading to an O (n!) time solution. The algorithm is cost-optimal, assuming the time to output the permutations is counted.

CONSTANT DELAY PARALLEL COUNTERS

1991 ◽  
Vol 01 (02) ◽  
pp. 143-148 ◽  
Author(s):  
SELIM G. AKL ◽  
THIBAULT DUBOUX ◽  
IVAN STOJMENOVIC
Keyword(s):  
Parallel Algorithm ◽  
Linear Array ◽  
Lexicographic Order ◽  
Constant Delay ◽  
Constant Size ◽  
Special Cases

We present a cost-optimal parallel algorithm for generating variations of m elements out of {0, 1, …, n - 1} in lexicographic order. It uses a linear array of m processors, each having constant size memory and each being responsible for producing one part of a given variation. Binary and decimal counters are special cases of the algorithm, when n = 2 and n = 10, respectively. To our knowledge, the algorithm presented here is the first to be published with the property that the delay between any two variations generated is constant.

Umatilla Virus Association with Fibrils and Tubules in Cultured Cells

1980 ◽  
Vol 38 ◽  
pp. 476-477
Author(s):  
Neil M. Foster ◽  
Ruth D. Breckon
Keyword(s):  
Bluetongue Virus ◽  
Linear Array ◽  
Cultured Cells ◽  
Intimate Association ◽  
Infected Cells ◽  
Dark Staining ◽  
In Cells

Macrotubules have been described1 in cells infected with Umatilla virus (UMAV), an orbivirus for which bluetongue virus (BTV) is the protype. Macrotubules, often in linear array, were observed in the cytoplasm and in intimate association with viroplasms of infected cells. Macrotubules had outside and inside diameters of 20 and 15 nm and many had dark-staining centers with diameters similar to the interiors of the tubules. UMAV was 60 nm and the RNA core was 30 nm in diameter. This report describes the association of UMAV with macrotubules and two types of microtubules.

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