2001The International Journal of High Performance Computing ApplicationsRequires access

Numerical Libraries and Tools for Scalable Parallel Cluster Computing

Jack Dongarra, Shirley Moore, Anne Trefethen

Open publisher page 9 citations

Abstract

For cluster computing to be effective within the scientific community it is essential that there are numerical libraries and programming tools available to application developers. Cluster computing may mean a cluster of heterogeneous components or hybrid architecture with some SMP nodes. This is clear at the high end, for example the latest IBM SP architecture, as well as in clusters of PC-based workstations. However, these systems may present very different software environments on which to build libraries and applications, and indeed require a new level of flexibility in the algorithms if they are to achieve an adequate level of performance. We will consider here the libraries and software tools that are already available and offer directions that might be taken in the light of cluster computing.

About this research paper

What this paper is about

For cluster computing to be effective within the scientific community it is essential that there are numerical libraries and programming tools available to application developers. Cluster computing may mean a cluster of heterogeneous components or hybrid architecture with some SMP nodes. This is clear at the high end, for example the latest IBM SP architecture, as well as in clusters of PC-based workstations. However, these systems may present very different software environments on which to build libraries and applications, and indeed require a new level of flexibility in the algorithms if they are to achieve an adequate level of performance. We will consider here the libraries and software tools that are already available and offer directions that might be taken in the light of cluster computing.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

For cluster computing to be effective within the scientific community it is essential that there are numerical libraries and programming tools available to application developers. Cluster computing may mean a cluster of heterogeneous components or hybrid architecture with some SMP nodes. This is clear at the high end, for example the latest IBM SP architecture, as well as in clusters of PC-based workstations. However, these systems may present very different software environments on which to build libraries and applications, and indeed require a new level of flexibility in the algorithms if they are to achieve an adequate level of performance. We will consider here the libraries and software tools that are already available and offer directions that might be taken in the light of cluster computing.

Key concepts: Computer science, Parallel computing, Scalability, Supercomputer, Computational science, Cluster (spacecraft), Computer cluster, GPU cluster

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