1996Wuhan University Journal of Natural SciencesRequires access

System support for parallel computing on heterogeneous networks of workstations

Xiaodong Zhang

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Abstract

In this paper, we introduce several on-going research projects to support parallel and distributed computing on heterogeneous networks of workstations (NOW) in the High Performance Computing and Software Laboratory at the University of Texas at San Antonio. The projects at aiming at addressing three technical issues. First, the factors of heterogeneity and time-sharing effects make traditional performance models/metrics for homogeneous computing performance measurement and evaluation not suitable for heterogeneous computing. We develop practical models and metrics which quantify the heterogeneity of networks and characterize the performance effects. Second, in order to perform parallel computation effectively, special system support is necessary. We are developing system schemes for heterogeneity management, process scheduling and efficient communications. Finally, to provide insight into system performance, we are developing two types of supporting tools: a graphical instrumentation monitor to aid users in investigating performance problems and in determining the most effective way of exploiting the NOW systems, and a trace-driven simulator to test and compare different system management and scheduling schemes.

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What this paper is about

In this paper, we introduce several on-going research projects to support parallel and distributed computing on heterogeneous networks of workstations (NOW) in the High Performance Computing and Software Laboratory at the University of Texas at San Antonio. The projects at aiming at addressing three technical issues. First, the factors of heterogeneity and time-sharing effects make traditional performance models/metrics for homogeneous computing performance measurement and evaluation not suitable for heterogeneous computing. We develop practical models and metrics which quantify the heterogeneity of networks and characterize the performance effects. Second, in order to perform parallel computation effectively, special system support is necessary. We are developing system schemes for heterogeneity management, process scheduling and efficient communications. Finally, to provide insight into system performance, we are developing two types of supporting tools: a graphical instrumentation monitor to aid users in investigating performance problems and in determining the most effective way of exploiting the NOW systems, and a trace-driven simulator to test and compare different system management and scheduling schemes.

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Available abstract

In this paper, we introduce several on-going research projects to support parallel and distributed computing on heterogeneous networks of workstations (NOW) in the High Performance Computing and Software Laboratory at the University of Texas at San Antonio. The projects at aiming at addressing three technical issues. First, the factors of heterogeneity and time-sharing effects make traditional performance models/metrics for homogeneous computing performance measurement and evaluation not suitable for heterogeneous computing. We develop practical models and metrics which quantify the heterogeneity of networks and characterize the performance effects. Second, in order to perform parallel computation effectively, special system support is necessary. We are developing system schemes for heterogeneity management, process scheduling and efficient communications. Finally, to provide insight into system performance, we are developing two types of supporting tools: a graphical instrumentation monitor to aid users in investigating performance problems and in determining the most effective way of exploiting the NOW systems, and a trace-driven simulator to test and compare different system management and scheduling schemes.

Key concepts: Computer science, Workstation, Distributed computing, Symmetric multiprocessor system, Scheduling (production processes), Heterogeneous network, Homogeneous, Software

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