Practical scalability assesment for parallel scientific numerical applications

• Main Authors: Perlin, Natalie, Zysman, Joel P, Kirtman, Ben P
• Format: Journal Article
• Language: English
• Published: 04.11.2016
• Subjects: Computer Science - Computational Engineering, Finance, and Science; Computer Science - Distributed, Parallel, and Cluster Computing; Physics - Atmospheric and Oceanic Physics
• DOI: 10.48550/arxiv.1611.01598

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.