How not to lie with statistics: the correct way to summarize benchmark results
Communications of the ACM - The MIT Press scientific computation series
Characterizing computer performance with a single number
Communications of the ACM
Computer architecture: a quantitative approach
Computer architecture: a quantitative approach
Measuring computer performance: a practitioner's guide
Measuring computer performance: a practitioner's guide
ACM SIGARCH Computer Architecture News
More on finding a single number to indicate overall performance of a benchmark suite
ACM SIGARCH Computer Architecture News
War of the benchmark means: time for a truce
ACM SIGARCH Computer Architecture News
The impact of speculative execution on SMT processors
International Journal of Parallel Programming
Accurately evaluating application performance in simulated hybrid multi-tasking systems
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
SubsetTrio: An evolutionary, geometric, and statistical benchmark subsetting framework
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Web based multi-platform benchmark program construction in smartphone
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Assessing computer performance with stocs
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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For several decades, computer scientists have been arguing which mean is more appropriate for summarizing computer performance: the harmonic or the geometric. We show that many test cases used in the past to discredit one mean or the other are either artificial or incidental. Changing only one of the benchmarks may result in totally different conclusions.In addition, we conclude that for the SPEC CPU2000 benchmark suite, the choice of averaging has very little influence on the relative standing of different machines. Therefore, the decision to purchase one system rather then another should not be influenced by the type of averaging used.