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27
Analyzing MarketBased Resource Allocation Strategies for the Computational Grid
 International Journal of High Performance Computing Applications
, 2001
"... In this paper, we investigate Gcommerce — computational economies for controlling resource allocation in Computational Grid settings. We define hypothetical resource consumers (representing users and Gridaware applications) and resource producers (representing resource owners who “sell ” their res ..."
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Cited by 101 (2 self)
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In this paper, we investigate Gcommerce — computational economies for controlling resource allocation in Computational Grid settings. We define hypothetical resource consumers (representing users and Gridaware applications) and resource producers (representing resource owners who “sell ” their resources to the Grid). We then measure the efficiency of resource allocation under two different market conditions: commodities markets and auctions. We compare both market strategies in terms of price stability, market equilibrium, consumer efficiency, and producer efficiency. Our results indicate that commodities markets are a better choice for controlling Grid resources than previously defined auction strategies. 1
Controlling the XenoServer Open Platform
, 2002
"... This paper presents the design of the XenoServer Open Platform: a public infrastructure for widearea computing, capable of hosting tasks that span the full spectrum of distributed programming. The platform integrates resource management, charging and auditing. We emphasize the controlplane aspects ..."
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Cited by 34 (14 self)
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This paper presents the design of the XenoServer Open Platform: a public infrastructure for widearea computing, capable of hosting tasks that span the full spectrum of distributed programming. The platform integrates resource management, charging and auditing. We emphasize the controlplane aspects of the system, showing how it supports service deployment with a low cost of entry and how it forms a substrate over which other distributed computing platforms can be deployed.
An Improved Semidefinite Programming Relaxation for the Satisfiability Problem
, 2002
"... The satisfiability (SAT) problem is a central problem in mathematical logic, computing theory, and artificial intelligence. An instance of SAT is specified by a set of boolean variables and a propositional formula in conjunctive normal form. Given such an instance, the SAT problem asks whether there ..."
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Cited by 14 (4 self)
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The satisfiability (SAT) problem is a central problem in mathematical logic, computing theory, and artificial intelligence. An instance of SAT is specified by a set of boolean variables and a propositional formula in conjunctive normal form. Given such an instance, the SAT problem asks whether there is a truth assignment to the variables such that the formula is satisfied. It is well known that SAT is in general NPcomplete, although several important special cases can be solved in polynomial time. Semidefinite programming (SDP) refers to the class of optimization problems where a linear function of a matrix variable X is maximized (or minimized) subject to linear constraints on the elements of X and the additional constraint that X be positive semidefinite. We are interested in the application of SDP to satisfiability problems, and in particular in how SDP can be used to detect unsatisfiability. In this paper we introduce a new SDP relaxation for the satisfiability problem. This SDP relaxation arises from the recently introduced paradigm of “higher liftings” for constructing semidefinite programming relaxations of discrete optimization problems.
Writing Programs that Run EveryWare on the Computational Grid
 IEEE Transactions on Parallel and Distributed Systems
, 2001
"... The Computational Grid [12] has been proposed for the implementation of highperformance applications using widely dispersed computational resources. The goal of a Computational Grid is to aggregate ensembles of shared, heterogeneous, and distributed resources (potentially controlled by separate org ..."
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Cited by 12 (6 self)
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The Computational Grid [12] has been proposed for the implementation of highperformance applications using widely dispersed computational resources. The goal of a Computational Grid is to aggregate ensembles of shared, heterogeneous, and distributed resources (potentially controlled by separate organizations) to provide computational “power ” to an application program. In this paper, we provide a toolkit for the development of globally deployable Grid applications. The toolkit, called EveryWare, enables an application to draw computational power transparently from the Grid. It consists of a portable set of processes and libraries that can be incorporated into an application so that a wide variety of dynamically changing distributed infrastructures and resources can be used together to achieve supercomputerlike performance. We provide our experiences gained while building the EveryWare toolkit prototype and an its use in implementing a largescale Grid application.
Data Staging Effects in Wide Area Task Farming Applications
 IEEE International Symposium on Cluster Computing and the grid
, 2001
"... Recent advances in computing and communication have given rise to the computational grid notion. The core of this computing paradigm is the design of a system for drawing compute power from a confederation of geographically dispersed heterogeneous resources, seamlessly and ubiquitously. If highperf ..."
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Cited by 11 (1 self)
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Recent advances in computing and communication have given rise to the computational grid notion. The core of this computing paradigm is the design of a system for drawing compute power from a confederation of geographically dispersed heterogeneous resources, seamlessly and ubiquitously. If highperformance levels are to be achieved, data locality must be identified and managed. In this paper, we consider the affect of server side staging on the behavior of a class of wide area “task farming ” applications. We show that staging improves task throughput mainly through the increased parallelism rather than the reduction in overall turnaround time per task. We derive a model for farming applications with and without server side staging and verify the model through live experiments as well as simulations. 1.
Gcommerce – building computational marketplaces for the computational grid
 University of Tennessee
, 2000
"... With the proliferation of the Internet comes the possibility of aggregating vast collections of computers into largescale computational platforms. Research driven by this realization has yielded a new software architecture, known as The Computational Grid [16], for building highperformance distribu ..."
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Cited by 9 (0 self)
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With the proliferation of the Internet comes the possibility of aggregating vast collections of computers into largescale computational platforms. Research driven by this realization has yielded a new software architecture, known as The Computational Grid [16], for building highperformance distributed applications and systems. The vision outlined by its architects is for applications to draw computational “power ” from a distributed pool of resources in
Optimization as an Internet resource
 Interfaces
, 2001
"... The rise of ecommerce promises particularly great benefits for the practice of largescale optimization. The World Wide Web already offers information, advice, and remote access to software for solving optimization problems. A variety of client programs are helping to increase the scope and conveni ..."
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Cited by 8 (4 self)
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The rise of ecommerce promises particularly great benefits for the practice of largescale optimization. The World Wide Web already offers information, advice, and remote access to software for solving optimization problems. A variety of client programs are helping to increase the scope and convenience of these tools. More sophisticated application service providers will further disseminate optimization modeling environments and solvers, making their power and variety readily available to a broader range of customers and applications.
Integrating Automatic Differentiation with ObjectOriented Toolkits for HighPerformance Scientific Computing
, 2000
"... Often the most robust and efficient algorithms for the solution of largescale problems involving nonlinear PDEs and optimization require the computation of derivative quantities. We examine the use of automatic differentiation (AD) to provide code for computing first and second derivatives in c ..."
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Cited by 4 (1 self)
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Often the most robust and efficient algorithms for the solution of largescale problems involving nonlinear PDEs and optimization require the computation of derivative quantities. We examine the use of automatic differentiation (AD) to provide code for computing first and second derivatives in conjunction with two parallel numerical toolkits, the Portable, Extensible Toolkit for Scientific Computing (PETSc) and the Toolkit for Advanced Optimization (TAO). We discuss how the use of mathematical abstractions for vectors and matrices in these libraries facilitates the use of AD to automatically generate derivative codes and present performance data demonstrating the suitability of this approach. 1 Introduction As the complexity of advanced computational science applications has increased, the use of objectoriented software methods for the development of both applications and numerical toolkits has also increased. The migration toward this approach can be attributed in part to ...
Sensitivity Analysis Using Parallel ODE Solvers and Automatic Differentiation in C: SensPVODE and ADIC
, 2000
"... PVODE is a highperformance ordinary differential equation solver for the types of initial value problems (IVPs) that arise in largescale computational simulations. Often, one wants to compute sensitivities with respect to certain parameters in the IVP. We discuss the use of automatic different ..."
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Cited by 4 (1 self)
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PVODE is a highperformance ordinary differential equation solver for the types of initial value problems (IVPs) that arise in largescale computational simulations. Often, one wants to compute sensitivities with respect to certain parameters in the IVP. We discuss the use of automatic differentiation (AD) to compute these sensitivities in the context of PVODE. Results on a simple test problem indicate that the use of ADgenerated derivative code can reduce the time to solution over finite difference approximations.
The NEOS Server for Optimization: Version 4 and Beyond
 Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL
, 2002
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