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We are largely interested in broad characterisation – and, ideally, in the ready-repeatability of the application of such benchmarks to other Cloud systems.
A reasonable number of such benchmarks are geared towards understanding performance of specific simulations or applications in the presence of low-latency (e.g. Infiniband, Myrinet) interconnects e.
An un-reflected adoption of such benchmarks then seems inadequate.
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Given the central role that Web services play today, the existence of such benchmark is a valuable tool when providing or consuming Web services.
One way consultants put skin in the game is to tie part of their fees to such benchmarks as cost savings or productivity increases.
Results of many such benchmarks are offered in isolation – e.g. LINPACK alone for Top500 supercomputers.
We present the Lehigh University Benchmark (LUBM) as an example of how to design such benchmarks.
Such benchmarks underpin trillions of dollars of financial products, including mortgages and student loans.
Although an MCID has been established for the Respiratory Symptoms scale [ 12], no such benchmarks for interpretation of change exist for the remaining CFQ-R scales.
Such benchmarks are used to determine the price of trillions of dollars of financial products, including mortgages and credit cards.
Remarkably, no such benchmarks currently exist.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com