Over the last years Transactional Memory (TM) gained growing popularity as a simpler, attractive alternative to classic lock-based synchronization schemes. Recently, the TM landscape has been profoundly changed by the integration of Hardware TM (HTM) in Intel commodity processors, raising a number of questions on the future of TM.We seek answers to these questions by conducting the largest study on TM to date, comparing different locking techniques, hardware and software TMs, as well as different combinations of these mechanisms, from the dual perspective of performance and power consumption.Our study sheds a mix of light and shadows on currently available commodity HTM: on one hand, we identify workloads in which HTM clearly outperforms any alternative synchronization mechanism; on the other hand, we show that current HTM implementations suffer of restrictions that narrow the scope in which these can be more effective than state of the art software solutions. Thanks to the results of our study, we identify a number of compelling research problems in the areas of TM design, compilers and self-tuning.

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Abstract-This paper addresses the issue of maximizing the efficiency and scalability of distributed transactional platforms, by introducing Bumper, a set of innovative techniques to minimize aborts of transactions in high-contention scenarios. At its core, Bumper relies on two key ideas: (1) sparing update transactions from spurious aborts when they access concurrently updated data, by attempting to serialize them in the past via a novel distributed concurrency control scheme that we call Distributed Time-Warping (DTW); and (2) avoiding aborts due to contention hot spots (that cannot be tackled by DTW) via a novel programming abstraction, called delayed actions, which allows to efficiently serialize, in an abort-free fashion, the execution of conflict-prone data manipulations.The techniques used in Bumper can be applied to a wide variety of transactional replication protocols to enhance their performance in contention intensive workloads. In this paper we show how they can be integrated with SCORe, a recent, highly-scalable genuine partial replication protocol. By means of an extensive evaluation using well-known benchmarks and a cluster of 160 nodes, we show that Bumper can boost performance up to 3x in conflict-intensive workloads, while imposing negligible (2.5%) overheads in uncontended scenarios.