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Book ChapterDOI

A Parallel Algorithm for Channel Routing

15 Jun 1988-pp 288-303
TL;DR: An optimal NC algorithm for 2-layer channel routing of VLSI designs is presented and an optimizing extension to the algorithm is given that resolves column conflicts under certain weak conditions and runs in polylog time.
Abstract: We present an optimal NC algorithm for 2-layer channel routing of VLSI designs. Our routing algorithm achieves channel density and runs in O(logn) time using O(n) processors on an EREW P-RAM. The routing algorithm is a parallel version of the widely used Left-Edge Algorithm. It can be used to solve the maximum clique and the minimum coloring problem for interval graphs and the maximum independent set problem for co-interval graphs with optimal processor-time bounds. We give an optimizing extension to our algorithm that resolves column conflicts under certain weak conditions and runs in polylog time. The routing algorithm can easily be implemented on a multi-processor shared-memory machine so our solution has considerable practical value.
Citations
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Book
06 Apr 1995
TL;DR: 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.
Abstract: 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.

533 citations


Cites methods from "A Parallel Algorithm for Channel Ro..."

  • ...They present an O(log n) time, n processor EREW-PRAM algorithm for two layer channel routing of VLSI designs in [318]....

    [...]

Proceedings ArticleDOI
24 Oct 1988
TL;DR: The author gives efficient parallel algorithms for recognizing chordal graphs, finding a maximum clique and a maximum independent set in a chordal graph, and an efficient parallel algorithm for finding a perfect elimination ordering.
Abstract: The author gives efficient parallel algorithms for recognizing chordal graphs, finding a maximum clique and a maximum independent set in a chordal graph, finding an optimal coloring of a chordal graph, finding a breadth-first search tree and a depth-first search tree of a chordal graph, recognizing interval graphs, and testing interval graphs for isomorphism. The key to the results is an efficient parallel algorithm for finding a perfect elimination ordering. >

74 citations

Journal ArticleDOI
TL;DR: A new parallel heuristic is described that on the 32K-processor CM-2 Connection Machine handles graphs with more than two million edges and gives in 9-min partitions that are within 2% of the best ever found.

51 citations

Proceedings Article
01 Jan 1990
TL;DR: This paper presents the first optimal, sublogarithmic algorithms for finding the Depth First Search and Breadth First Search trees of an interval graph.

11 citations

Journal ArticleDOI
TL;DR: A new parallel algorithm for the minimum coloring problem on interval graphs is developed that is both easy to understand and easy to implement.

7 citations

References
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Book
01 Jan 1980
TL;DR: This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems and remains a stepping stone from which the reader may embark on one of many fascinating research trails.
Abstract: Algorithmic Graph Theory and Perfect Graphs, first published in 1980, has become the classic introduction to the field. This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems. It remains a stepping stone from which the reader may embark on one of many fascinating research trails. The past twenty years have been an amazingly fruitful period of research in algorithmic graph theory and structured families of graphs. Especially important have been the theory and applications of new intersection graph models such as generalizations of permutation graphs and interval graphs. These have lead to new families of perfect graphs and many algorithmic results. These are surveyed in the new Epilogue chapter in this second edition. New edition of the "Classic" book on the topic Wonderful introduction to a rich research area Leading author in the field of algorithmic graph theory Beautifully written for the new mathematician or computer scientist Comprehensive treatment

4,090 citations

Proceedings ArticleDOI
30 Apr 1968
TL;DR: To achieve high throughput rates today's computers perform several operations simultaneously; not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computing operations are done concurrently.
Abstract: To achieve high throughput rates today's computers perform several operations simultaneously. Not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computing operations are done concurrently. A major problem in the design of such a computing system is the connecting together of the various parts of the system (the I/O devices, memories, processing units, etc.) in such a way that all the required data transfers can be accommodated. One common scheme is a high-speed bus which is time-shared by the various parts; speed of available hardware limits this scheme. Another scheme is a cross-bar switch or matrix; limiting factors here are the amount of hardware (an m × n matrix requires m × n cross-points) and the fan-in and fan-out of the hardware.

2,553 citations

Journal ArticleDOI
TL;DR: A recurstve construction is used to obtain a product circuit for solving the prefix problem and a Boolean clrcmt which has depth 2[Iog2n] + 2 and size bounded by 14n is obtained for n-bit binary addmon.
Abstract: The prefix problem is to compute all the products x t o x2 . . . . o xk for i ~ k .~ n, where o is an associative operation A recurstve construction IS used to obtain a product circuit for solving the prefix problem which has depth exactly [log:n] and size bounded by 4n An application yields fast, small Boolean ctrcmts to simulate fimte-state transducers. By simulating a sequentml adder, a Boolean clrcmt which has depth 2[Iog2n] + 2 and size bounded by 14n Is obtained for n-bit binary addmon The size can be decreased significantly by permitting the depth to increase by an addmve constant

1,159 citations

Journal ArticleDOI
Richard Cole1
TL;DR: A parallel implementation of merge sort on a CREW PRAM that uses n processors and O(logn) time; the constant in the running time is small.
Abstract: We give a parallel implementation of merge sort on a CREW PRAM that uses n processors and $O(\log n)$ time; the constant in the running time is small. We also give a more complex version of the algorithm for the EREW PRAM; it also uses n processors and $O(\log n)$ time. The constant in the running time is still moderate, though not as small.

847 citations

Proceedings ArticleDOI
01 Dec 1983
TL;DR: A sorting network of size 0(n log n) and depth 0(log n) is described, and a derived procedure (&egr;-nearsort) are described below, and the sorting network will be centered around these elementary steps.
Abstract: The purpose of this paper is to describe a sorting network of size 0(n log n) and depth 0(log n). A natural way of sorting is through consecutive halvings: determine the upper and lower halves of the set, proceed similarly within the halves, and so on. Unfortunately, while one can halve a set using only 0(n) comparisons, this cannot be done in less than log n (parallel) time, and it is known that a halving network needs (½)n log n comparisons. It is possible, however, to construct a network of 0(n) comparisons which halves in constant time with high accuracy. This procedure (e-halving) and a derived procedure (e-nearsort) are described below, and our sorting network will be centered around these elementary steps.

683 citations