scholarly journals A Brief Survey of Fixed-Parameter Parallelism

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 197
Author(s):  
Faisal N. Abu-Khzam ◽  
Karam Al Kontar
Keyword(s):  
Parallel Algorithms ◽  
General View ◽  
Search Trees ◽  
Color Coding ◽  
Parallel Complexity ◽  
Fixed Parameter ◽  
New Directions ◽  
Iterative Compression ◽  
Bounded Search Trees

This paper provides an overview of the field of parameterized parallel complexity by surveying previous work in addition to presenting a few new observations and exploring potential new directions. In particular, we present a general view of how known FPT techniques, such as bounded search trees, color coding, kernelization, and iterative compression, can be modified to produce fixed-parameter parallel algorithms.

Bounded Search Trees

2015 ◽  
pp. 51-76
Author(s):  
Marek Cygan ◽  
Fedor V. Fomin ◽  
Łukasz Kowalik ◽  
Daniel Lokshtanov ◽  
Dániel Marx ◽  
...  
Keyword(s):  
Search Trees ◽  
Bounded Search Trees

EFFICIENT PARALLEL ALGORITHMS FOR TEMPLATE MATCHING

2002 ◽  
Vol 12 (03n04) ◽  
pp. 359-364 ◽  
Author(s):  
SANGUTHEVAR RAJASEKARAN
Keyword(s):  
Parallel Algorithms ◽  
Template Matching ◽  
Efficient Algorithms ◽  
Parallel Complexity

The parallel complexity of template matching has been well studied. In this paper we present more work-efficient algorithms than the existing ones. Our algorithms are based on FFT primitives. We consider the following models of computing: PRAM and the hypercube.

Closing Remarks

1995 ◽  
Author(s):  
Raymond Greenlaw ◽  
H. James Hoover ◽  
Walter L. Ruzzo
Keyword(s):  
Parallel Algorithms ◽  
Parallel Algorithm ◽  
Parallel Computers ◽  
Massively Parallel ◽  
Parallel Complexity ◽  
Square Roots ◽  
Np Completeness ◽  
Massively Parallel Computers ◽  
Input Size ◽  
The Relationship

The previous chapters have laid out the history, foundations, and mechanics of the theory of P-completeness. We have shown that this theory plays roughly the same role in the parallel complexity domain as , NP-completeness does in the sequential domain. Having devoted much effort to establishing the notion of feasible highly parallel algorithms and arguing that P-completeness captures the notions of inherently sequential problems and algorithms, it is now appropriate to temper our case a bit with some additional observations. For some problems depending on the relevant input size, it may not be worth the effort to search for a feasible highly parallel algorithm assuming for example that you already have a √n time parallel algorithm. The following table shows the relationship between square roots and logarithms for various input sizes. Of course, for small input sizes the constants on the running times also play a major role. Although it is extremely risky to predict hardware trends, it seems safe to say that massively parallel computers containing billions of processors are not "just around the corner" and although potentially feasible, machines with millions of processors are not soon to become commodity personal computers. Thus, highly parallel algorithms will not be feasible if the processor requirements for an input of size n are much greater than n2, and probably more like n log n. Even if you have sufficient numbers of processors for problems that interest you, your algorithm may succumb to the tyranny of asymptotics. For example, a parallel algorithm that uses √n time is probably preferable to one that uses (logn)4 time, at least for values of n less than 1013. As Table 11.1 illustrates, the only really practical polylogarithmic parallel time algorithms are O((logn)2). Perhaps the limit to feasible highly parallel algorithms are those that run in (logn)2 time and use O(n2) processors. However, the search for an NC algorithm often leads to new insights into how a problem can be effectively parallelized. That is, a problem frequently is found to exhibit unexpected parallelism when the limits of its parallelism are pushed.

ON PARALLEL RECOGNITION OF TWO CLASSES OF 2-D ARRAY PATTERNS

1992 ◽  
Vol 06 (02n03) ◽  
pp. 293-299
Author(s):  
WOJCIECH RYTTER ◽  
AHMED SAOUDI
Keyword(s):  
Parallel Algorithms ◽  
Time Complexity ◽  
Regular Array ◽  
Parallel Complexity ◽  
Context Free

We investigate the parallel complexity of recognition problems for context-free and regular array (image) sets. We show that the sequential time complexity of the recognition of an n × n image is O(n5). The space required for these recognition problems is O(n5). We prove that there are log 2n time parallel algorithms with BM (n4) and n2 BM (n) processors for the recognition of context-free and regular array sets, respectively, where BM (n) is the number of processors sufficient to multiply two boolean n × n matrices in logarithmic time. We develop also a methodology for processing images using composition systems.

Sociocultural memory development research drives new directions in gadgetry science

2019 ◽  
Vol 42 ◽  
Author(s):  
Penny Van Bergen ◽  
John Sutton
Keyword(s):  
Episodic Memory ◽  
Autobiographical Memory ◽  
Developmental Psychology ◽  
Cross Cultural ◽  
Memory Development ◽  
Development Research ◽  
Cultural Research ◽  
New Directions ◽  
Cross Cultural Research

Abstract Sociocultural developmental psychology can drive new directions in gadgetry science. We use autobiographical memory, a compound capacity incorporating episodic memory, as a case study. Autobiographical memory emerges late in development, supported by interactions with parents. Intervention research highlights the causal influence of these interactions, whereas cross-cultural research demonstrates culturally determined diversity. Different patterns of inheritance are discussed.

Statistical Study of the Rotation Effect of Am Stars

1976 ◽  
Vol 32 ◽  
pp. 675-683
Author(s):  
Keiichi Kodaira
Keyword(s):  
Statistical Study ◽  
Rotation Velocity ◽  
General View ◽  
Slow Rotation ◽  
Rotation Effect

SummaryExcess of [m1] index of Am stars, relative to normal stars, is statistically found to be correlated with rotation velocity; the coefficient is estimated at ∆׀m1׀ /∆V(km/sec) ˜ - 0.0007 among Am stars. This result supports the general view that slow rotation is essential for Am phenomena.

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