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On the other hand, the subscale Health Problems was identified as a weak scale (Hs = 0.35).
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Scale-H, Loevingers coefficient of homogeneity and scalability are classified as follow: 0.30 – 0.39 indicates a weak scale, 0.40 – 0.50 indicates moderate scalability and > 0.50 indicates strong scale.
H values < 0.30 are considered to reflect a poor item and values for the scale as a whole are interpreted as follows: H values in the range 0.30 0.40 reflect a weak scale, 0.40 0.50 a medium scale and H > 0.50 reflects a strong scale.
For scales, the values of Hs can be considered as follows [ 1]: Hs > 0.3 indicates a weak scale Hs > 0.4 indicates a moderate scale Hs > 0.5 indicates a strong scale.
*Interpretation Loevinger's scaling coefficients: Hs of 0.30 - 0.40 indicates a weak scale; Hs of 0.40 – 0.50 indicates a moderate scale; Hs >0.50 indicates a strong scale.
Hs > 0.3 indicates a weak scale Hs > 0.4 indicates a moderate scale Hs > 0.5 indicates a strong scale.
A Loevinger's scalability coefficient (H) of 0.30 - 0.39 indicates a weak scale, H 0.40 - 0.49 indicates a moderate scale, and H ≥ 0.50 indicates a strong scale [ 39].
Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99% efficiency as long as the number of GPUs and L increase together.
For the uniform mesh generation, we observed a weak scaling speedup of 163.8 and above for up to 256 cores as opposed to PODM whose weak scaling speedup is only 44.7 on 256 cores.
We tested PDR.POD Mon Blacklight, a distributed shared memory (DSM) machine in the Pittsburgh Supercomputing Center, and observed a weak scaling speedup of 163.8 and above for up to 256 cores as opposed to PODM whose weak scaling speedup is only 44.7 on 256 cores.
Fuzzy scales were introduced as a transition between weak scales and strong scales.
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