A good benchmarking methodology can save a tremendous amount of resources in terms of human effort, machine cycles, and cost. Such a methodology must consider the relevance and openness of the chosen codes, well-defined rules for executing and reporting the benchmarks, a review process to enforce the rules, and a public repository for the obtained information. For the methodology to be feasible, it must also be supported by adequate tools that enable the user to consistently execute the benchmarks and gather the requisite metrics. At the very least, reliable benchmarking results can help people make decisions about HPC acquisitions and assist scientists and engineers in system advances. By saving resources and enabling balanced designs and configurations, realistic benchmarking ultimately leads to increased competitiveness in both industry and academia.
Published in:
Computing in Science & Engineering
(Volume:10
,
Issue:
4
)
Date of Publication: July-Aug. 2008