Open AccessBook
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. 0201548569B04062001read more
Citations
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Journal ArticleDOI
Characterization of Efficiently Parallel Solvable Problems on Distance-Hereditary Graphs
TL;DR: A general problem-solving paradigm is developed that solves these problems efficiently in parallel and also obtains new linear-time algorithms by a sequential simulation of the authors' parallel algorithms.
Proceedings ArticleDOI
An On-Demand Fast Parallel Pseudo Random Number Generator with Applications
TL;DR: This paper investigates a CPU+GPU hybrid technique to create an efficient PRNG that can produce random numbers on demand as opposed to a onetime generation and applies it to design a list ranking algorithm and a Monte Carlo simulation which shows the high quality of the generator.
Journal ArticleDOI
Language and library support for practical PRAM programming
TL;DR: Fork95 as discussed by the authors is a parallel programming language for the Parallel Random Access Machine (PRAM) model of parallel computation, which is used in the SB-PRAM project at the University of Saarbrucken.
Proceedings ArticleDOI
A static workload balance scheduling algorithm
TL;DR: An efficient load balance scheduling algorithm is developed assuming that the workload has certain properties and some computational results are given for the product between an upper diagonal matrix and a vector.
Proceedings ArticleDOI
Power-Performance Comparison of Single-Task Driven Many-Cores
TL;DR: This work sets the power envelope as a constraint and evaluates an envisioned 1024-core XMT processor against an NVIDIA GTX280 GPU considering various scenarios for estimating the power of the XMT chip, showing that the X MT processor sustains its advantage over the GPU on irregular parallel programs, while not falling significantly behind on regular programs.
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,Faye A. Briggs +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
W. Daniel Hillis,Guy L. Steele +1 more
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
Steven Fortune,James C. Wyllie +1 more
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.