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An introduction to parallel algorithms

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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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DissertationDOI

The reconfigurable mesh : programming model, self-simulation, adaptability, optimality, and applications

TL;DR: This thesis contributes to the acceptance of the reconfigurable mesh as the architecture of the next generation massively parallel computer by focusing on programming, algorithmic, scaling, and optimality issues.
Proceedings ArticleDOI

Parallel pattern identification in biological sequences on clusters

TL;DR: This paper presents a low communication-overhead parallel algorithm for pattern identification in biological sequences, and concludes an algorithm with five computation/communication phases, each requiring O(n) computation time and only O(p) message units.
Proceedings ArticleDOI

A Parallel MPI I/O Solution Supported by Byte-addressable Non-volatile RAM Distributed Cache.

TL;DR: Results of experiments suggest, that the MPI I/O extension based on in-system distributed cache with data located in Non-volatile Random Access Memory (NVRAM) available in each cluster node significantly reduces file access time, especially for smallI/O operations.
Proceedings ArticleDOI

On the relaxed synchronization for massively parallel numerical algorithms

TL;DR: A novel relaxed synchronization strategy for generic numerical algorithms executed in distributed and parallel computing systems and it is shown that with this relaxation, the numerical algorithm converges faster to the same fixed-point value than the conventional implementation.
Posted Content

Memory Aware Load Balance Strategy on a Parallel Branch-and-Bound Application

TL;DR: In this paper, the authors proposed the multicore cluster model (MCM) which captures the most relevant performance characteristics in multicores systems such as the influence of memory hierarchy and contention.
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.