A Performance Model of the Parallel Ocean Program

Abstract

In this paper we describe a performance model of the Parallel Ocean Program (POP). In particular, the latest version of POP (v2.0) is considered, which has similarities and differences to the earlier version (v1.4.3) as commonly used in climate simulations. The performance model encapsulates an understanding of POP’s data decomposition, processing flow, and scaling characteristics. The model is parametrized in many of the main input parameters to POP as well as characteristics of a processing system such as network latency and bandwidth. The performance model has been validated to date on a medium-sized (128 processor) AlphaServer ES40 system with the QsNet-1 interconnection network, and also on a larger scale (2048 processor) Blue Gene/Light system. The accuracy of the performance model is high when using two standard benchmark configurations, one of which represents a realistic configuration similar to that used in Community Climate System Model coupled climate simulations. The performance model is also used to explore the performance of POP after possible optimizations to the code, and different task to processor assignment strategies, whose performance cannot be currently measured.