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Machine Learning-Based Self-Adjusting Concurrency in Software Transactional Memory Systems
2012
2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Software Transactional Memories (STM) are a promising paradigm for parallel programming on multicore platforms. One of the problems of STM systems is the performance degradation that can be experienced when applications run with a non-optimal concurrency level, namely number of concurrent threads. When this level is too high a loss of performance may occur due to excessive data contention and consequent transaction aborts. Conversely, if concurrency is too low, the performance may be penalized
doi:10.1109/mascots.2012.40
dblp:conf/mascots/RughettiSCQ12
fatcat:4rgm3f37tzg5zdudspbkrsctxm