The cost of privatization in software transactional memory

Software transactional memory (STM) is a promising approach for programming concurrent applications; STM guarantees that a transaction, consisting of a sequence of operations on the memory, appears to execute atomically. In practice, however, it is important to be able to run transactions together with nontransactional legacy code accessing the same memory locations, by supporting privatization of shared data. Privatization should be provided without sacrificing the parallelism offered by today's multicore systems and multiprocessors. This paper proves an inherent cost for supporting privatization, which is linear in the number of privatized items. Specifically, we show that a transaction privatizing k items must have a data set of size at least k, in an STM with invisible reads, which is oblivious to different nonconflicting executions and guarantees progress in such executions. When reads are visible, it is shown that r memory locations must be accessed by a privatizing transaction, where r is the minimum between k, the number of privatized items, and the number of concurrent transactions guaranteed to make progress. This captures, in a concrete and quantitative manner, the tradeoff between the cost of privatization and the level of parallelism offered by the STM.