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Experimental results show that the average speedup is 1.36 times faster than default Linux scheduler through evaluation using PARSEC benchmarks, demonstrating that the proposed technique is promising when compared to other prior studies.
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Experiments over controlled benchmarks demonstrated that the algorithms' performances are problem dependent [50, 51].
Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking.
Experimental results on the Middlebury stereo benchmarks demonstrate the effectiveness of the proposed approach.
Performance benchmarks demonstrate model execution in around 100 milliseconds on consumer hardware.
Simulation results and comparisons based on benchmarks demonstrate the effectiveness of the HGA.
HSPICE simulation results using ISCAS benchmarks demonstrate the efficacy of the presented design methods.
Extensive experiments on widely used benchmarks demonstrate that our proposal remarkably outperforms state-of-the-arts.
Finally, simulations and comparisons based on benchmarks demonstrate the effectiveness and efficiency of the proposed HDE.
Simulations and comparisons based on well-known benchmarks demonstrate the efficiency, effectiveness, and robustness of the proposed HDE.
Computer benchmarks demonstrate the speedup of our implementation over the CPU implementation as well as strong and weak scalability.
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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