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An introduction to parallel algorithms

TLDR
This book provides an introduction to the design and analysis of parallel algorithms, with the emphasis on the application of the PRAM model of parallel computation, with all its variants, to algorithm analysis.
Abstract
Written by an authority in the field, this book provides an introduction to the design and analysis of parallel algorithms. The emphasis is on the application of the PRAM (parallel random access machine) model of parallel computation, with all its variants, to algorithm analysis. Special attention is given to the selection of relevant data structures and to algorithm design principles that have proved to be useful. Features *Uses PRAM (parallel random access machine) as the model for parallel computation. *Covers all essential classes of parallel algorithms. *Rich exercise sets. *Written by a highly respected author within the field. 0201548569B04062001

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Posted Content

Parallel Search with Extended Fibonacci Primitive

TL;DR: This paper first model the random walk using extended Fibonacci series generator and reveals that search primitive with pointer jumping is better than the other two primitives.
Proceedings ArticleDOI

Parallel Computing: Unplugging to Learn

TL;DR: A new methodology for teaching parallel computing for young beginners in programming is proposed, based on principles of unplugged computing, like to learn doing and playing, which can be very useful in teaching the difficult concepts of parallel computing.
Proceedings ArticleDOI

Exact Inference on Manycore Processors using Pointer Jumping

TL;DR: Experimental results show that, for junction trees with limited data and structural parallelism, pointer jumping is well suited to accelerate exact inference on manycore systems.

Simulations and Algorithms on Reconfigurable Meshes With Pipelined Optical Buses.

TL;DR: This dissertation presents a meta-analyses of the reconstruction and Contributions of the LARPBS, the CF-LR-Mesh, and the P R -M esh, and some of the algorithms used in these models to derive the values of these models.
Dissertation

Design, implementation and evaluation of a distributed CDCL framework

TL;DR: A distributed, CDCL-based framework for SAT solving, and several combinations of simplification techniques that can solve instances which could not be solved by the DDC algorithm alone.
References
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Book

Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes

TL;DR: This chapter discusses sorting on a Linear Array with a Systolic and Semisystolic Model of Computation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually sorting arrays.
Book

Computer Architecture and Parallel Processing

Kai Hwang, +1 more
TL;DR: The authors have divided the use of computers into the following four levels of sophistication: data processing, information processing, knowledge processing, and intelligence processing.
Journal ArticleDOI

Data parallel algorithms

TL;DR: The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.
Proceedings ArticleDOI

Parallelism in random access machines

TL;DR: A model of computation based on random access machines operating in parallel and sharing a common memory is presented and can accept in polynomial time exactly the sets accepted by nondeterministic exponential time bounded Turing machines.
Journal ArticleDOI

The Parallel Evaluation of General Arithmetic Expressions

TL;DR: It is shown that arithmetic expressions with n ≥ 1 variables and constants; operations of addition, multiplication, and division; and any depth of parenthesis nesting can be evaluated in time 4 log 2 + 10(n - 1) using processors which can independently perform arithmetic operations in unit time.