Abstract
The concept of scalability analysis of numerical parallel applications has
been revisited, with the specific goals defined for the performance estimation
of research applications. A series of Community Climate Model System (CCSM)
numerical simulations were used to test the several MPI implementations,
determine optimal use of the system resources, and their scalability. The
scaling capacity and model throughput performance metrics for $N$ cores showed
a log-linear behavior approximated by a power fit in the form of $C(N)=bN^a$,
where $a$ and $b$ are two empirical constants. Different metrics yielded
identical power coefficients ($a$), but different dimensionality coefficients
($b$). This model was consistent except for the large numbers of N. The power
fit approach appears to be very useful for scalability estimates, especially
when no serial testing is possible. Scalability analysis of additional
scientific application has been conducted in the similar way to validate the
robustness of the power fit approach.