Brian Borchers

The Lanczos Method: Evolution and Application, by Louis Komzsik

The information hiding philosophy of object-oriented programming encourages localizing data structures within objects rather than sharing data globally across different classes of objects. This emphasis on local data leads naturally to fine-grained data abstractions, particularly in scientific simulations involving large collections of small, discrete physical or mathematical objects. This paper focuses on a subset of such simulations where dynamically reconfigurable links bind the objects together. It is demonstrated that fine-grained data structures reduce the complexity of local operations on the data at the potential expense of increased global operation complexity. Two metrics are used to describe data structures: granularity is the number of instantiations required to cover the data space, whereas extent is the continuously traversable length of the data along a given direction. These definitions are applied to two abstractions for simulating the turbulent motion of quantum vortices in superfluid liquid helium. Several local and global operations on a fine-grained linked list are compared with those on a coarse-grained array. It is demonstrated that fine-grained data structures recover the simplicity of more coarse-grained structures if maximal extent is maintained as the granularity increases.

Damian W.I. Rouson

Yi Xiong

Design Metrics in Quantum Turbulence Simulations: How Physics Influences Software Architecture

In this work we make a strong case for remote memory access (RMA) as the effective way to program a parallel computer by proposing a framework that supports RMA in a library independent, simple and intuitive way. If one uses our approach the parallel code one writes will run transparently under MPI-2 enabled libraries but also bulk-synchronous parallel libraries. The advantage of using RMA is code simplicity, reduced programming complexity, and increased efficiency. We support the latter claims by implementing under this framework a collection of benchmark programs consisting of a communication and synchronization performance assessment program, a dense matrix multiplication algorithm, and two variants of a parallel radix-sort algorithm and examine their performance on a LINUX-based PC cluster under three different RMA enabled libraries: LAM MPI, BSPlib, and PUB. We conclude that implementations of such parallel algorithms using RMA communication primitives lead to code that is as efficient as the message-passing equivalent code and in the case of radix-sort substantially more efficient. In addition our work can be used as a comparative study of the relevant capabilities of the three libraries.

Alexandros V. Gerbessiotis

Seung-Yeop Lee

Remote Memory Access: A Case for Portable, Efficient and Library Independent Parallel Programming

We present models for bartering of resources on grids. Bartering models can be useful for making resource allocation decisions in grids and perhaps even for building a so called barter grid whereby distributed resources such as electronic media can be bartered. Grids allow various resources to be shared among many users. This sharing however definitely does not mean that everyone will have unrestricted use of the resources. Some mechanism such as pricing or quotas can be employed in order to enforce controlled sharing of resources. A barter model for resource sharing can enable people or computer centers to directly get something in return for letting their resources to be used by others. We utilize directed hypergraphs to develop a barter model in which multiple resources can be traded. We prove that the decision version of the multi-resource bartering problem is NP-complete. We present an integer programming formulation for the bartering problem. We also present a linear time algorithm to compute components that may contain feasible bartering solutions. We generalize our multi-resource bartering formulation to the case where multiple instances of resources are present. Finally, we present various computational results from our software that makes use of LP_SOLVE and CPLEX mixed integer programming libraries to solve example bartering problems.

Can &#xd6;zturan

Resource Bartering in Data Grids

Runge-Kutta methods are popular methods for the solution of ordinary differential equations and implementations are provided by many scientific libraries. The performance of Runge-Kutta methods depends on the specific application problem to be solved, but also on the characteristics of the target machine. For processors with a memory hierarchy, the locality of data referencing pattern has a large impact on the efficiency of a program. In this paper, we describe program transformations for Runge-Kutta methods resulting in implementations with improved locality behavior for systems of ODEs. The transformations are based on properties of the solution method but are independent from the specific application problem or the specific target machine so that the resulting implementation is suitable as library function. We show that the locality improvement leads to performance gains on different recent microprocessors.

Thomas Rauber

Gudula R&#xfc;nger

Improving Locality for ODE Solvers by Program Transformations

It is difficult to solve design optimization problems of complex systems by using a traditional computing method because complex simulation processes usually lead to large-scale computation. Therefore the distributed computing technology based on decomposition-coordination theory has received much attention by design engineers. This paper studies a peer-to-peer collaborative optimization method based on distributed computing technology in order to examine flexible optimization. A new distributed collaborative optimization framework is proposed, and a coordination method is developed and used to deal with the conflict of related variables among sub-optimization problems. A multi-agent based distributed computing environment is implemented. The implementation of an optimization agent, in which CORBA technology is used to implement communication between the components of the optimization agent, is discussed in detail. Two examples are used to demonstrate the efficiency of the computing method and the reliability and flexibility of the multi-agent system.

Caijun Xue

Hong Nie

Qingying Qiu

Peien Feng

A Peer-to-Peer Distributed Collaborative Optimization System

In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed active contour image segmentation model. We propose integrating aspects of the classic algorithm to improve the active contour model. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.

J.R. Rommelse

H.X. Lin

T.F. Chan

Efficient Active Contour and K-Means Algorithms in Image Segmentation

We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad&#x7e;hoc networks. Three components of this framework, namely a mobility data generator (MDG), a graph structure generator (GSG) and an occlusion modification tool (OMT) allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG) which generates packet transmission activities for transceivers and a packet activity simulator (PAS) which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility) proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS) developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of transceivers) and variation in time as transceivers move in space.

Chris Barrett

Martin Drozda

Madhav V. Marathe

S.S. Ravi

James P. Smith

A Mobility and Traffic Generation Framework for Modeling and Simulating Ad Hoc Communication Networks

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Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

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Chief Editor&nbsp;Professor Tramontana&nbsp;is based at the University of Catania and his research primarily concerns the areas of software engineering and distributed systems.

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Scientific Programming - Table of contents 2004

title

Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

Scientific Programming