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About 10,000 papers for “Distributed and Parallel Computing Systems”

PARALLEL AND DISTRIBUTED COMPUTING AND SYSTEMS

2008

An Introduction to New Extensions for Stochastic Activity Networks Stochastic activity networks (SANs) are a powerful and flexible extension of Petri nets. However, SANs facilities are not enough for modeling and analysis of complex and large-scale systems. In order to provide such high-level

Cited by 0

Dynamical Parallel Applications on Distributed and High Performance Computing Systems

Claus-Peter Rückemann · 2009

This paper provides an extended overview of recent dvelopments for exploiting distributed, Grid and High Per-formance Computing (HPC) resources with applications like Geoscientific Information Systems (GIS) based on the GISIG actmap-project. Focus is on frameworks for optimising the dynamical parallel use of computing resources for future cooperation and development concepts, integrating software and hardware architecture aspects. Using parallel processing and the method of event triggering from within Active Source can be used to exploit the vast computing power of distributed MultiCore parallel systems for a multitude of purposes like geoinformation processing, geophysical data analysis, information systems, and e-Science. An extended case study for an application InfoPoint demonstrates the algorithm here. As various obstacles showed up with implementing and minimising the complexity of the application-resource workflow, the creation of future Web and HPC services on top of HPC and Distributed Systems will be a solution for dedicated issues. The new extended framework of the Grid-GIS house is presented here, showing the case study for using these concepts for exploration purposes. For implementation testing distributed resources and the new multisite supercomputer resources of HLRN-II (North-German Supercomputing Alliance) have been used.

Cited by 0

Robust resource allocation in heterogeneous parallel and distributed computing systems

J.T. Smith, Siegel, H. J., Maciejewski, A. A. · Colorado State University · 2008

In a heterogeneous distributed computing environment, it is often advantageous to allocate system resources in a manner that optimizes a given system performance measure. However, this optimization is often dependent on system parameters whose values are subject to uncertainty. Thus, an important research problem arises when system resources must be allocated given uncertainty in system parameters. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. In this research, we define mathematical models of robustness in both static and dynamic stochastic environments. In addition, we model dynamic environments where estimates of system parameter values are provided as point estimates where these estimates are known to deviate substantially from their actual values. The main contributions of this research are (1) mathematical models of robustness suitable for dynamic environments based on single estimates of system parameters (2) a mathematical model of robustness applicable to environments where the uncertainty in system parameters can be modeled stochastically, (3) a demonstration of the use of this metric to design resource allocation heuristics in a static environment, (4) a mathematical model of robustness in a stochastic dynamic environment, (5) we demonstrate the utility of this dynamic robustness metric through the design of resource allocation heuristics, (6) the derivation of a robustness metric for evaluating resource allocation decisions in an overlay network along with a near optimal resource allocation technique suitable to this environment.

Cited by 0Open access

System Level Fault Tolerance in Parallel and Distributed Computing Systems

Defense Technical Information Center (DTIC) · 1993

The major thrust of our effort was focused on the theory and practice of responsive (fault-tolerant, real-time) computing in parallel and distributed processing environments. New efficient methods of system testing have been developed which shorten a multiprocessor testing time by orders of magnitude and, therefore, can be used at system booting (previous techniques were prohibitively long. A new design framework for responsive computing was designed and is being implemented for validation. This framework for responsive computing was designed and is being implemented for validation. This framework is based on consensus which can be used to provide synchronization, reliable communication, fault diagnosis, checkpointing and even scheduling in multiprocessor environments. We have formalized and quantified the space-time tradeoff for efficient fault recovery. The system model is a graph, and we were especially successful in analysis of meshes and hypercubes. We developed a new method called naturally redundant algorithms which allows efficient implementation of application-specific techniques

Cited by 0