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Exact(10)
QPALMA's runtime appears to be dominated by its splice site scoring algorithm; its authors estimate that mapping 71 million RNA-Seq reads to A.thaliana would take 400 CPU hours, which is ∼180 000 reads per CPU hour.
Difficult instances with up to 50 potential plants and 100 customers, and largest easy instances, can be solved in one CPU hour.
> -wrap-foot> To normalise for different sequence lengths, we report millions of DNA bases processed per CPU hour.
This indicates an average of ∼190 252 reads mapped per CPU minute, or ∼11.4 million reads mapped per CPU hour.
TopHat maps reads to splice sites in a mammalian genome at a rate of ∼2.2 million reads per CPU hour.
Specifically, we chose to base our comparison on the cost per CPU hour because it provided the most equivalent metric for comparing running-time costs.
Similar(50)
Currently, the average CPU time for small proteins is about 5 CPU hours for I-TASSER, whereas the CPU cost for the atomic ROSETTA modeling is 150 CPU days per target.
The optimization took 1.03 CPU hours and the optimum design parameters are obtained.
Fig. 8 Computational cost as measured in CPU hours for each code and benchmark.
However, in general, better models require larger training sets, which in turn require more CPU hours.
We assess model computation cost by comparing the total CPU hours required for the model runs for each benchmark (Fig. 8).
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