TL;DR
This paper discusses designing cost-effective Beowulf clusters tailored for specific computational problems by combining theoretical code analysis and benchmarking to optimize hardware configurations.
Contribution
It introduces a method for designing optimized Beowulf clusters based on theoretical and empirical analysis specific to targeted applications.
Findings
Theoretical analysis guides hardware selection for clusters.
Benchmarking on similar hardware improves design accuracy.
Optimized clusters reduce costs while maintaining performance.
Abstract
Small Beowulf clusters can effectively serve as personal or group supercomputers. In such an environment, a cluster can be optimally designed for a specific problem (or a small set of codes). We discuss how theoretical analysis of the code and benchmarking on similar hardware lead to optimal systems.
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