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Neither of the implementations achieved good results.
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Table 2.11 shows the classification scheme and the implementation achieved in relation to the long-term goals.
The evaluation results for these implementations achieved two times speedup over the serial one [5].
The implementation achieves much better performance than conventional processing systems, with a speedup of more than 890 times on NVIDIA Tesla C1060 supercomputing cards compared to an Intel P4 2.4 GHz CPU.
The implementation achieves both soundness and completeness.
The CTC implementation achieved 21.46% saving in power consumption for the VOPD benchmark.
The MPI implementation achieved good speedup values, up to 30 times the serial code using 50 cores.
The reported WUR implementation achieved the power consumption of 37.5 μW and has sensitivity of −62.7 dBm.
Each study was assessed independently by GE and IS and categorized according to the intervention described and the level of implementation achieved, using an adapted model of implementation; see Table 1[ 22] 22].
For most of the instances of a research library of problems, the ruin and recreate (R&R) implementation achieved the best published results.
We do acknowledge that lack of detail and data made it difficult to assess the "degree of implementation" achieved; see Additional file 3, Table S2.
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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