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Optimal simulations of tree machines

Sandeep Bhatt, Fan Chung, Tom Leighton, Arnold L. Rosenberg

Open publisher page 163 citations

Abstract

Universal networks offer the advantage that they can execute programs written for simpler architectures without significant run-time overhead. In this paper we investigate simulations of tree machines; the fact that divide-and-conquer algorithms are programmed naturally on trees motivates our investigation. Among various proposals for parallel computing the boolean hypercube has emerged as a particularly versatile network. It is well known that programs for multidimensional grid machines, for example, can be executed on a hypercube with no communications overhead by embedding the grid as a subgraph of the hypercube. Our first result is that a program for any tree machine can be executed on the hypercube with constant overhead. More precisely, every cycle of a synchronous binary tree can be simulated in O(1) cycles on a hypercube, independent of the shape of the tree. The algorithm to embed the tree within the hypercube runs in polynomial time. We also give efficient simulations of arbitrary binary trees on the complete binary tree, the FFT and shuffle-exchange networks. It is natural to ask if any sparse network can simulate every binary tree efficiently. Somewhat surprisingly, we construct a universal bounded-degree network on N nodes for which every N node binary tree is a spanning tree. In other words, every binary tree can be simulated on our universal network with no overhead. This improves previous bounds on the sizes of universal graphs for trees.

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What this paper is about

Universal networks offer the advantage that they can execute programs written for simpler architectures without significant run-time overhead. In this paper we investigate simulations of tree machines; the fact that divide-and-conquer algorithms are programmed naturally on trees motivates our investigation. Among various proposals for parallel computing the boolean hypercube has emerged as a particularly versatile network. It is well known that programs for multidimensional grid machines, for example, can be executed on a hypercube with no communications overhead by embedding the grid as a subgraph of the hypercube. Our first result is that a program for any tree machine can be executed on the hypercube with constant overhead. More precisely, every cycle of a synchronous binary tree can be simulated in O(1) cycles on a hypercube, independent of the shape of the tree. The algorithm to embed the tree within the hypercube runs in polynomial time. We also give efficient simulations of arbitrary binary trees on the complete binary tree, the FFT and shuffle-exchange networks. It is natural to ask if any sparse network can simulate every binary tree efficiently. Somewhat surprisingly, we construct a universal bounded-degree network on N nodes for which every N node binary tree is a spanning tree. In other words, every binary tree can be simulated on our universal network with no overhead. This improves previous bounds on the sizes of universal graphs for trees.

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Available abstract

Universal networks offer the advantage that they can execute programs written for simpler architectures without significant run-time overhead. In this paper we investigate simulations of tree machines; the fact that divide-and-conquer algorithms are programmed naturally on trees motivates our investigation. Among various proposals for parallel computing the boolean hypercube has emerged as a particularly versatile network. It is well known that programs for multidimensional grid machines, for example, can be executed on a hypercube with no communications overhead by embedding the grid as a subgraph of the hypercube. Our first result is that a program for any tree machine can be executed on the hypercube with constant overhead. More precisely, every cycle of a synchronous binary tree can be simulated in O(1) cycles on a hypercube, independent of the shape of the tree. The algorithm to embed the tree within the hypercube runs in polynomial time. We also give efficient simulations of arbitrary binary trees on the complete binary tree, the FFT and shuffle-exchange networks. It is natural to ask if any sparse network can simulate every binary tree efficiently. Somewhat surprisingly, we construct a universal bounded-degree network on N nodes for which every N node binary tree is a spanning tree. In other words, every binary tree can be simulated on our universal network with no overhead. This improves previous bounds on the sizes of universal graphs for trees.

Key concepts: Hypercube, Computer science, Binary tree, Overhead (engineering), Tree (set theory), Self-balancing binary search tree, K-ary tree, Parallel computing

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