A Study of Conflict Detection in Software Transactional Memory
Daniel Lupei · TSpace (University of Toronto) · 2010
Transactional Memory (TM) has been proposed as a simpler parallel programming model compared to the traditional locking model. However, uptake from the programming community has been slow, primarily because performance issues of software-based TM strategies are not well understood. In this thesis we conduct a systematic analysis of conflict scenarios that may emerge when enforcing correctness between conflicting transactions. We find that some combinations of conflict detection and resolution strategies perform better than others depending on the conflict patterns in the application. We validate our findings by implementing several concurrency control strategies, and by measuring their relative performance. Based on these observations, we introduce partial rollbacks as a mechanism for effectively compensating the variability in the TM algorithm performance. We show that using this mechanism we can obtain close to the overall best performance for a range of conflict patterns in a synthetically generated workload and a realistic game application.