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Full-Text Articles in Physical Sciences and Mathematics

Modeling And Comparison Of Wormhole Routed Mesh And Torus Networks, Ronald I. Greenberg, Lee Guan Oct 1997

Modeling And Comparison Of Wormhole Routed Mesh And Torus Networks, Ronald I. Greenberg, Lee Guan

Computer Science: Faculty Publications and Other Works

2D-mesh and torus networks have often been proposed as the interconnection pattern for parallel computers. In addition, wormhole routing has increasingly been advocated as a method of reducing latency. Most analysis of wormhole routed networks, however, has focused on the torus and the broader class of k-ary n-cubes to which it belongs. This paper presents a performance model for the wormhole routed mesh, and it compares the performance of the mesh and torus based on theoretical and empirical analyses.


Fast Discrete Polynomial Transforms With Applications To Data Analysis For Distance Transitive Graphs, J. R. Driscoll, D. M. Healy, D. N. Rockmore Aug 1997

Fast Discrete Polynomial Transforms With Applications To Data Analysis For Distance Transitive Graphs, J. R. Driscoll, D. M. Healy, D. N. Rockmore

Dartmouth Scholarship

Let $\poly = \{P_0,\dots,P_{n-1}\}$ denote a set of polynomials with complex coefficients. Let $\pts = \{z_0,\dots,z_{n-1}\}\subset \cplx$ denote any set of {\it sample points}. For any $f = (f_0,\dots,f_{n-1}) \in \cplx^n$, the {\it discrete polynomial transform} of f (with respect to $\poly$ and $\pts$) is defined as the collection of sums, $\{\fhat(P_0),\dots,\fhat(P_{n-1})\}$, where $\fhat(P_j) = \langle f,P_j \rangle = \sum_{i=0}^{n-1} f_iP_j(z_i)w(i)$ for some associated weight function w. These sorts of transforms find important applications in areas such as medical imaging and signal processing.

In this paper, we present fast algorithms for computing discrete orthogonal polynomial transforms. For a system …


An Improved Analytical Model For Wormhole Routed Networks With Application To Butterfly Fat-Trees, Ronald I. Greenberg, Lee Guan Aug 1997

An Improved Analytical Model For Wormhole Routed Networks With Application To Butterfly Fat-Trees, Ronald I. Greenberg, Lee Guan

Computer Science: Faculty Publications and Other Works

A performance model for wormhole routed interconnection networks is presented and applied to the butterfly fat-tree network. Experimental results agree very closely over a wide range of load rate. Novel aspects of the model, leading to accurate and simple performance predictions, include (1) use of multiple-server queues, and (2) a general method of correcting queuing results based on Poisson arrivals to apply to wormhole routing. These ideas can also be applied to other networks.


Dynamic Load Distribution In Mist, K. Al-Saqabi, R. M. Prouty, Dylan Mcnamee, Steve Otto, Jonathan Walpole Jul 1997

Dynamic Load Distribution In Mist, K. Al-Saqabi, R. M. Prouty, Dylan Mcnamee, Steve Otto, Jonathan Walpole

Computer Science Faculty Publications and Presentations

This paper presents an algorithm for scheduling parallel applications in large-scale, multiuser, heterogeneous distributed systems. The approach is primarily targeted at systems that harvest idle cycles in general-purpose workstation networks, but is also applicable to clustered computer systems and massively parallel processors. The algorithm handles unequal processor capacities, multiple architecture types and dynamic variations in the number of processes and available processors. Scheduling decisions are driven by the desire to minimize turnaround time while maintaining fairness among competing applications. For efficiency, the virtual processors (VPs) of each application are gang scheduled on some subset of the available physical processors.


Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan Apr 1997

Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan

Electrical & Computer Engineering Faculty Research

This paper studies the applicability of Kalman filtering approaches for network wide traveler origin-destination estimation from link traffic volumes. The paper evaluates the modeling assumptions of the Kalman filters and examines the implications of such assumptions.


Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay Apr 1997

Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.


Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan Mar 1997

Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

This paper introduces a hybrid system termed cascade adaptive resonance theory mapping (ARTMAP) that incorporates symbolic knowledge into neural-network learning and recognition. Cascade ARTMAP, a generalization of fuzzy ARTMAP, represents intermediate attributes and rule cascades of rule-based knowledge explicitly and performs multistep inferencing. A rule insertion algorithm translates if-then symbolic rules into cascade ARTMAP architecture. Besides that initializing networks with prior knowledge can improve predictive accuracy and learning efficiency, the inserted symbolic knowledge can be refined and enhanced by the cascade ARTMAP learning algorithm. By preserving symbolic rule form during learning, the rules extracted from cascade ARTMAP can be compared …


Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow Feb 1997

Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Neural Logic Network (NLN) is a class of neural network models that performs both pattern processing and logical inferencing. This article presents a procedure for NLN to learn multi-dimensional mapping of both binary and analog data. The procedure, known as the Supervised Clustering and Matching (SCM) algorithm, provides a means of inferring inductive knowledge from databases. In contrast to gradient descent error correction methods, pattern mapping is learned by an inductive NLN using fast and incremental clustering of input and output patterns. In addition, learning/encoding only takes place when both the input and output match criteria are satisfied in a …


Minimizing Channel Density With Movable Terminals, Ronald I. Greenberg, Jau-Der Shih Feb 1997

Minimizing Channel Density With Movable Terminals, Ronald I. Greenberg, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

We give algorithms to minimize density for VLSI channel routing problems with terminals that are movable subject to certain constraints. The main cases considered are channels with linear order constraints, channels with linear order constraints and separation constraints, channels with movable modules containing fixed terminals, and channels with movable modules and terminals. In each case, we improve previous results for running time and space by a factor of L/\lgn and L, respectively, where L is the channel length, and n is the number of terminals.


Genetic Algorithms For The Extended Gcd Problem, Jonathan P. Sorenson Jan 1997

Genetic Algorithms For The Extended Gcd Problem, Jonathan P. Sorenson

Scholarship and Professional Work - LAS

We present several genetic algorithms for solving the extended greatest common divisor problem. After defining the problem and discussing previous work, we will state our results.


Adaptive Multicast Routing In Wormhole Networks, Ran Libeskind-Hadas, Tom Hehre '96, Andrew Hutchings '98, Mark Reyes '98, Kevin Watkins '97 Jan 1997

Adaptive Multicast Routing In Wormhole Networks, Ran Libeskind-Hadas, Tom Hehre '96, Andrew Hutchings '98, Mark Reyes '98, Kevin Watkins '97

All HMC Faculty Publications and Research

Multicast communication has applications in a number of fundamental operations in parallel computing. An effective multicast routing algorithm must be free from both livelock and deadlock while minimizing communication latency. We describe two classes of multicast wormhole routing algorithms that employ the multi-destination wormhole hardware mechanism proposed by Lin et al. [12] and Panda et al. [17]. Specific examples of these classes of algorithms are described and experimental results suggests that such algorithms enjoy low communication latencies across a range of network loads.


Resolution Of Local Inconsistency In Identification, Douglas Ray Anderson, Martin Zwick Jan 1997

Resolution Of Local Inconsistency In Identification, Douglas Ray Anderson, Martin Zwick

Systems Science Faculty Publications and Presentations

This paper reports an algorithm for the resolution of local inconsistency in information-theoretic identification. This problem was first pointed out by Klir as an important research area in reconstructability analysis. Local inconsistency commonly arises when an attempt is made to integrate multiple data sources, i.e., contingency tables, which have differing common margins. For example, if one ha)s an AB table and a BC table, the B margins obtained from the two tables may disagree. If the disagreement can be assigned to sampling error, then one can arrive at a compromise B margin, adjust the original AB and BC tables to …


Parallel Algorithms For Single-Layer Channel Routing, Ronald I. Greenberg, Shih-Chuan Hung, Jau-Der Shih Jan 1997

Parallel Algorithms For Single-Layer Channel Routing, Ronald I. Greenberg, Shih-Chuan Hung, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

We provide efficient parallel algorithms for the minimum separation, offset range, and optimal offset problems for single-layer channel routing. We consider all the variations of these problems that are known to have linear- time sequential solutions rather than limiting attention to the "river-routing" context, where single-sided connections are disallowed. For the minimum separation problem, we obtain O(lgN) time on a CREW PRAM or O(lgN / lglgN) time on a (common) CRCW PRAM, both with optimal work (processor- time product) of O(N), where N is the number of terminals. For the offset range problem, we obtain the same time and processor …