Abstract
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.
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Index Terms
Modeling transactional memory workload performance
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Modeling transactional memory workload performance
PPoPP '10: Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel ProgrammingTransactional 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 ...
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