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Note: These benchmarks were performed immediately after unboxing the computer with a reboot between each one.
The micro benchmarks were performed to validate the use under heavy computational tasks.
All benchmarks were performed on CentOS Linux 7.4 running on virtualized Intel Haswell CPUs clocked at 2.6 GHz with 512 GB RAM; benchmarked software parts were run single-threaded.
Timing benchmarks were performed on a dual IntelR CoreTM CPU 6700 (2.6 GHz) PC running Windows 7 Enterprise Service Pack 1 with 2.00 GB of RAM using single CPU per command line script.
The benchmarks were performed on the Fastra II, the Fastra I, a 512-core cluster (consisting of Opteron CPUs), an Nvidia Tesla C1060 workstation card on an Intel Core i7 940 CPU, and on an Intel Core i7 940 CPU itself.
Benchmarks were performed using a measure of similarity between the Gene Ontology (GO) terms of each functionally associated protein pair predicted in the query genome by each method.
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Computational results on classical CFD benchmarks are performed.
Extensive analysis of these approaches with SPEC and PARSEC benchmarks are performed using a full system simulator.
For a proper validation of the code, four benchmarks are performed using one-dimensional dynamic analytical solutions developed by the authors.
These benchmarks are performed in the companion paper [33].
Therefore, accuracy benchmarks are performed in order to verify that the round-off errors are reasonable (see, for example, [13]).
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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