Hardware Transactional Memory (HTM) offers the opportunity to ease parallel programming. However, driven by hardware limitations, commercial implementations eschew the complexity involved in early sophisticated proposals from academia, and, among other things, opt for simple conflict resolution policies that inevitably increase transaction aborts. To increase thread level parallelism, previous works propose conflict resolution schemes that, instead of aborting, add a second level of speculation consisting in using not-yet-committed data from another transaction. This policy, which we refer to as requester-speculates, has not yet been considered in the context of the kind of best-effort HTM support provided by commercial processors. This work proposes CHAining TransactionS (CHATS), a simple yet effective realization of the requester-speculates con-flict resolution policy in which cyclic dependencies between transactions are avoided and the commit ordering respects the dependencies that transactions make once speculative values are communicated. The ultimate result is a best-effort HTM implementation that forces a partial order between transactions in a way that ensures effective utilization of forwarded data and that gets away from the complexity of previous proposals. Simulations using gem5 demonstrate the effectiveness of CHATS in both commercial-like setups and academic state-of-the-art best-effort systems (22% and 16% reduction in execution time, on average, respectively). These improvements are achieved by requiring less than 280 bytes of extra storage.

Hardware Transactional Memory (HTM) allows the use of transactions by programmers, making parallel programming easier and theoretically obtaining the performance of fine-grained locks. However, transactions can abort for a variety of reasons, resulting in the squash of speculatively executed instructions and the consequent loss in both performance and energy efficiency. Among the different sources of abort, conflicting concurrent accesses to the same shared memory locations from different transactions are often the prevalent cause.In this work, we characterize, for the first time to the best of our knowledge, how the aggressiveness of the cores in terms of exploiting instruction-level parallelism can interact with thread-level speculation support brought by HTM systems. We observe that altering the size of the structures that support out-of-order and speculative execution changes the number of aborts produced in the execution of transactional workloads on a best-effort HTM implementation. Our results show that a small number of powerful cores is more suitable for high-contention scenarios, whereas under low contention it is preferable to use a larger number of less aggressive cores. In addition, an aggressive core can lead to performance loss in medium-contention scenarios due to an increase in the number of aborts. We conclude that depending on contention, a careful choice over processor aggressiveness can reduce abort ratios.