Modeling transactional memory workload performance

Transactional memory promises to make parallel programming easier than with fine-grained locking, while performing just as well. This performance claim is not always borne out because an application may violate a common-case assumption of the TM designer or because of external system effects. In order to help programmers assess the suitability of their code for transactional memory, this work introduces a formal model of transactional memory as well as a tool, called Syncchar. Syncchar can predict the speedup of a conversion from locks to transactions within 25% for the STAMP benchmarks. Because getting good performance from transactions is more difficult than commonly appreciated, developers need tools to tune transactional performance.