Evaluating the impact of the programming model on the performance and complexity of software DSM systems

Abstract

In this paper we evaluate the impact of the programming model on the performance and complexity of Entry Consistency-based software distributed shared-memory systems (software DSMs). We study three novel software DSMs that can all take advantage of lock-style primitives but impose different variations of the shared-memory programming model. The first variation is a plain shared-memory model based on barriers and mutual exclusion locks, where the association between shared data and lock variables is determined transparently by the system. The second model dictates that all accesses to shared data must be delimited by lock/unlock-type primitives (with or without mutual exclusion), even though the lock-data association is still performed transparently. The third model requires that all shared data accesses be delimited by lock/unlock-type primitives and the association between locks and data is specified explicitly by the programmer. A comparison of our software DSMs shows that increasing the model complexity simplifies the systems substantially. Our results also show that the second model can perform significantly worse than the first model, while the third model improves performance by 25% and 27% on average compared to the first and second models, respectively. We conclude that increasing the burden on the programmer is not necessarily a good option for software DSMs; only the most elaborate model we study achieves performance that justifies its programming complexity.