Software pipelining is an aggressive scheduling technique that generates efficient code for loops and is particularly effective for VLIW architectures. Few software pipelining algorithms, however, are able to efficien...
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ISBN:
(纸本)9780818676413
Software pipelining is an aggressive scheduling technique that generates efficient code for loops and is particularly effective for VLIW architectures. Few software pipelining algorithms, however, are able to efficiently schedule loops that contain conditional branches. We have developed an algorithm we call All Paths Pipelining (APP) that addresses this shortcoming of software pipelining. APP is designed to achieve optimal or near-optimal performance for any run of iterations while providing efficient code for transitioning between runs. A run is the execution of consecutive iterations that all execute the same path through a loop. APP accomplishes this by using techniques from modulo scheduling and kernel recognition algorithms, the two main approaches for software pipelining loops. We have implemented the APP algorithm in our research compiler and have evaluated its performance by executing its generated code on a VLIW instruction-set simulator. For a processor with five heterogeneous functional units, APP is able to add another 1% to 23% increase in performance over basic software pipelining by effectively pipelining loops with conditional branches.
An upper bound for the trade-off between space and routing time and space needed to store routing information in the processors and the packets is proven. This result is a consequence of a new strategy for the simulat...
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An upper bound for the trade-off between space and routing time and space needed to store routing information in the processors and the packets is proven. This result is a consequence of a new strategy for the simulation between arbitrary networks. Finally, several techniques are applied for the simulation of networks to demonstrate space-efficiently routing strategies for vertex-symmetric networks.
We describe a new randomized parallel algorithm for computing the planar convex hull of n points on a p processor-memory pair machine communicating through a network for which O(log p) routing is possible. We show tha...
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We describe a new randomized parallel algorithm for computing the planar convex hull of n points on a p processor-memory pair machine communicating through a network for which O(log p) routing is possible. We show that the algorithm has optimal O(n log n/p) performance provided that p = o(n/log3n). We report extensive computational experience with the algorithm which supports its theoretical claims.
We implemented and measured several methods to perform BMMC permutations on the MasPar MP-2. Our results indicate that, except for certain types of permutations or very high virtual processor ratios, the best method o...
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We implemented and measured several methods to perform BMMC permutations on the MasPar MP-2. Our results indicate that, except for certain types of permutations or very high virtual processor ratios, the best method overall is the naive method but with virtual-processor numbers computed in Gray-code order. For some permutations, however, the naive method performs very poorly;the best method in these cases is an adaptation of the block BMMC algorithm for parallel disk systems in which the processor elements are treated as independent devices.
Emerging applications in multi-media and the Human Genome Project require storage and searching of large databases of strings - a task for which parallelism seems the only hope. In this paper, we consider the parallel...
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Emerging applications in multi-media and the Human Genome Project require storage and searching of large databases of strings - a task for which parallelism seems the only hope. In this paper, we consider the parallelism in some of the fundamental problems in compressing strings and in matching large dictionaries of patterns against texts. We present the first work-optimal algorithms for these well-studied problems including the classical dictionary matching problem, optimal compression with a static dictionary and the universal data compression with dynamic dictionary of Lempel and Ziv. All our algorithms are randomized and they are of the Las Vegas type. Furthermore, they are fast, working in time logarithmic in the input size. Additionally, our algorithms seem suitable for a distributed implementation.
Consider the following NP-hard problems: Given a graph G, find the minimum 2-edge connected and 2-vertex connected subgraphs spanning all vertices of G. The past few years have produced exciting sequential algorithms ...
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ISBN:
(纸本)9780897917179
Consider the following NP-hard problems: Given a graph G, find the minimum 2-edge connected and 2-vertex connected subgraphs spanning all vertices of G. The past few years have produced exciting sequential algorithms for approximating such minimum subgraphs [6, 7]. The approximation factors are improved from 2 down to 5/4 and 3/2 respectively. Yet the techniques involved are all based on augmenting depth-first-search trees and no similar progress has been carried to the parallel context. This paper presents NC algorithms to achieve approximation factors of 3/2 + Ε and 7/4 + Ε respectively without computing depth-first-search trees.
This paper provides a new approach to labeling the connected components of an n × n image on a scan line array processor (comprised of n processing elements). Variations of this approach yield an algorithm guaran...
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ISBN:
(纸本)9780897917179
This paper provides a new approach to labeling the connected components of an n × n image on a scan line array processor (comprised of n processing elements). Variations of this approach yield an algorithm guaranteed to complete in o(n lg n) time as well as algorithms likely to approach O(n) time for all or most images. The best previous solutions require using a more complicated architecture or require Ω(n lg n) time. We also show that on a restricted version of the architecture, any algorithm requires Ω(n lg n) time in the worst case.
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