Optimizing Persistent Transactions (Brief Announcement)
Tingzhe Zhou, Pantea Zardoshti, Michael Spear · 2019
There is a mechanical transformation by which algorithms for software transactional memory can be transformed to work with persistent memory. While correct, this transformation does not take into account differences between the persistent and volatile programming models. We show that fundamental properties of the data regions accessed by a persistent software transaction allow for a variety of optimizations not available in the volatile setting, and these lead to significant performance gains.