Publisher Summary
This chapter discusses parallel algorithms for shared-memory machines. Parallel computation is rapidly becoming a dominant theme in all areas of computer science and its applications. It is estimated that, within a decade, virtually all developments in computer architecture, systems programming, computer applications and the design of algorithms will be taking place within the context of parallel computation. In preparation for this revolution, theoretical computer scientists have begun to develop a body of theory centered on parallel algorithms and parallel architectures. As there is no consensus yet on the appropriate logical organization of a massively parallel computer, and as the speed of parallel algorithms is constrained as much by limits on interprocessor communication as it is by purely computational issues, it is not surprising that a variety of abstract models of parallel computation have been pursued. Closest to the hardware level are the VLSI models, which focus on the technological limits of today's chips, in which gates and wires are packed into a small number of planar layers.

Parallel algorithms for shared-memory machines

Kurskod: 5DV050 Inrättad: 2008-03-31 Inrättad av: teknisk-naturvetenskapliga fakultetsnämnden Reviderad: 2012-02-29 Reviderad av: teknisk-naturvetenskapliga fakultetsnämnden Kursplan giltig från: 2012, vecka 10 Ansvarig enhet: Inst för datavetenskap SCB-ämnesrubrik: Informatik/Dataoch systemvetenskap Huvudområden och successiv fördjupning: Beräkningsteknik: Avancerad nivå, har endast kurs/er på grundnivå som förkunskapskrav (A1N) , Datavetenskap: Avancerad nivå, har endast kurs/er på grundnivå som förkunskapskrav (A1N) Betygsskala: För denna kurs ges betygen 5 Med beröm godkänd, 4 Icke utan beröm godkänd, 3 Godkänd, VG Väl godkänd, G Godkänd, U Underkänd Utbildningsnivå: Avancerad nivå

The design and analysis of parallel algorithms

We define the notion of a well-separated pair decomposition of points in d-dimensional space We then develop efficient sequential and parallel algorithms for computing such a decomposition We apply the resulting decomposition to the efficient computation of k-nearest neighbors and n-body potential fields

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A decomposition of multidimensional point sets with applications to k-nearest-neighbors and n-body potential fields

This volume provides an ideal introduction to key topics in parallel computing. With its cogent overview of the essentials of the subject as well as lists of P -complete- and open problems, extensive remarks corresponding to each problem, a thorough index, and extensive references, the book will prove invaluable to programmers stuck on problems that are particularly difficult to parallelize. In providing an up-to-date survey of parallel computing research from 1994, Topics in Parallel Computing will prove invaluable to researchers and professionals with an interest in the super computers of the future.

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Limits to Parallel Computation: P-Completeness Theory

We present efficient parallel algorithms for several basic problems in computational geometry: convex hulls, Voronoi diagrams, detecting line segment intersections, triangulating simple polygons, minimizing a circumscribing triangle, and recursive data-structures for three-dimensional queries.

Parallel computational geometry

A simple parallel tree contraction algorithm

A solution to the hidden surface elimination problem called Beam Tracing is described. Beam tracing is related to ray tracing but uses spatial coherence within the scene, and area coherence within the image to batch computations. Beam tracing is an object space solution to the hidden surface problem.Beam tracing is formulated in terms of its principal subprocesses: intersection, sorting, and clipping. A Hierarchical Scene Representation is proposed. This incorporates the space decomposition idea of the BSP tree [Fuchs, Kedem and Naylor, 80] along with the convex polytope intersection detection technique of [Dobkin and Kirkpatrick, 83] to interleave and efficiently solve the intersection and sorting subproblems of beam tracing.

The geometry of beam tracing

The study of parallelism in computational geometry has been largely confined to individual case studies and isolated results with the exception of the recent comprchcnsivc paper of Aggarwal CI al [ACGOY]. Aggarwal et al presented a number of techniques and tools which have laid the foundation for the study of parallelism in computational geometry. Among their results were parallel solutions to such familiar geometric problems as convex hull construction (in 2 and 3-d). Voronoi diagram construction (in 2-d) and closest point search, and segment intersecti&. More recently, Atallah and Goodrich [AG] elaborated on one technique which they proposed (parallel plane sweep).

Norm Dadoun

Papers

A simple parallel tree contraction algorithm

The geometry of beam tracing

Parallel processing for efficient subdivision search

Parallel Construction of Subdivision Hierarchies

Optimal Parallel Algorithms for Convex Polygon Separation