2004International Conference on SupercomputingRequires access

Cluster operating system support for parallel autonomic computing

Andrzej Gościński, J. Silcock, Michael Hobbs

Open publisher page 5 citations

Abstract

The aim of this paper is to show a general design of autonomic elements and initial implementation of a cluster operating system that moves parallel processing on clusters to the computing mainstream using the autonomic computing vision. The significance of this solution is as follows. Autonomic Computing was identified by IBM as one of computing's Grand Challenges. The human body was used to illustrate an Autonomic Computing system that possesses self-knowledge, self-configuration, self optimization, self-healing, and self-protection, knowledge of its environment and user friendliness properties. One of the areas that could benefit from the comprehensive approach created by the autonomic computing vision is parallel processing on non-dedicated clusters. Many researchers and research groups have responded positively to the challenge by initiating research around one or two of the characteristics identified by IBM as the requirements for autonomic computing. We demonstrate here that it is possible to satisfy all Autonomic Computing characteristics.

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What this paper is about

The aim of this paper is to show a general design of autonomic elements and initial implementation of a cluster operating system that moves parallel processing on clusters to the computing mainstream using the autonomic computing vision. The significance of this solution is as follows. Autonomic Computing was identified by IBM as one of computing's Grand Challenges. The human body was used to illustrate an Autonomic Computing system that possesses self-knowledge, self-configuration, self optimization, self-healing, and self-protection, knowledge of its environment and user friendliness properties. One of the areas that could benefit from the comprehensive approach created by the autonomic computing vision is parallel processing on non-dedicated clusters. Many researchers and research groups have responded positively to the challenge by initiating research around one or two of the characteristics identified by IBM as the requirements for autonomic computing. We demonstrate here that it is possible to satisfy all Autonomic Computing characteristics.

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Available abstract

The aim of this paper is to show a general design of autonomic elements and initial implementation of a cluster operating system that moves parallel processing on clusters to the computing mainstream using the autonomic computing vision. The significance of this solution is as follows. Autonomic Computing was identified by IBM as one of computing's Grand Challenges. The human body was used to illustrate an Autonomic Computing system that possesses self-knowledge, self-configuration, self optimization, self-healing, and self-protection, knowledge of its environment and user friendliness properties. One of the areas that could benefit from the comprehensive approach created by the autonomic computing vision is parallel processing on non-dedicated clusters. Many researchers and research groups have responded positively to the challenge by initiating research around one or two of the characteristics identified by IBM as the requirements for autonomic computing. We demonstrate here that it is possible to satisfy all Autonomic Computing characteristics.

Key concepts: Autonomic computing, Computer science, IBM, End-user computing, Supercomputer, Data-intensive computing, Distributed computing, Computer cluster

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