This paper explores data speculation for improving the performance of Hardware Transactional Memory (HTM). We attempt to reduce transactional conflicts by decoupling them from cache coherence conflicts; many HTMs do not distinguish between transactional conflicts and coherence conflicts, leading to false transactional conflicts. We also attempt to mitigate the effects of coherence conflicts by using value prediction in transactions. We show that coherence decoupling and value prediction in transactions complement each other, because they both speculate on data in ways that are infeasible in the absence of HTM support.

Widespread adoption of Phase Change Memory (PCM) requires solutions to several problems recently addressed in the literature, including limited endurance, increased write latencies, and system-level changes required to exploit non-volatility. One important difference between PCM and DRAM that has received less attention is the increased need for write power management. Writing to a PCM cell requires high current density over hundreds of nanoseconds, and hard limits on the number of simultaneous writes must be enforced to ensure correct operation, limiting write throughput and therefore overall performance. Because several wear reduction schemes only write those bits that need to be written, the amount of power required to write a cache line back to memory under such a system is now variable, which creates opportunity to reduce write power. This paper proposes policies that monitor the bits that have actually been changed over time, as opposed to simply those lines that are dirty. These polices can more effectively allocate power across the system to improve write concurrency. This method for allocating power across the memory subsystem is built on the idea of "power tokens," a transferable, but time-specific, allocation of power. The results show that with a storage overhead of 4.3% in the last-level cache, a power-aware memory system can improve the performance of multiprogrammed workloads by up to 84%.

This paper introduces NZTM, a nonblocking, zero-indirection, object-based, hybrid transactional memory system. NZTM comprises a nonblocking software transactional memory (STM) system that can exploit best-effort hardware transactional memory (HTM) if available to improve performance.