COS: A Parallel Performance Model for Dynamic Variations in Processor Speed, Memory Speed, and Thread Concurrency

Highly-parallel, high-performance scientific applications must maximize performance inside of a power envelope while maintaining scalability. Emergent parallel and distributed systems offer a growing number of operating modes that provide unprecedented control of processor speed, memory latency, and memory bandwidth. Optimizing these systems for performance and power requires an understanding of the combined effects of these modes and thread concurrency on execution time. In this paper, we describe how an analytical performance model that separates pure computation time (C) and pure stall time (S) from computation-memory overlap time (O) can accurately capture these combined effects. We apply the COS model to predict the performance of thread and power mode combinations to within 7% and 17% for parallel applications (e.g. LULESH) on Intel x86 and IBM BG/Q architectures, respectively. The key insight of the COS model is that the combined effects of processor and memory throttling and concurrency on overlap trend differently than the combined effects on pure computation and pure stall time. The COS model is novel in that it enables independent approximation of overlap which leads to capabilities and accuracies that are as good or better than the best available approaches.