Modeling and measuring multiprogramming and system overheads on a shared-memory multiprocessor: Case study

This paper presents methodologies capable of quantifying multiprogramming (MP) overhead on a computer system. Two methods which quantify the lower bound on MP overhead, along with a method to determine MP overhead present in real workloads, are introduced. The techniques are illustrated by determining the percentage of parallel processing time consumed by MP overhead on Alliant multiprocessors. The real workload MP overhead measurements, as well as measurements of other overhead components such as kernel lock spinning, are then used in a comprehensive case study of performance degradation due to overheads. It is found that MP overhead accounts for well over half of the total system overhead. Kernel lock spinning is determined to be a major component of both MP and total system overhead. Correlation analysis is used to uncover underlying relationships between overheads and workload characteristics. It is found that for the workloads studied, MP overhead in the parallel environment is not statistically dependent on the number of parallel jobs being multiprogrammed. However, because of increased kernel contention, serial jobs, even those executing on peripheral processors, are responsible for variation in MP overhead.