This article presents Pot, a system that leverages the concept of preordered transactions to achieve deterministic multithreaded execution of programs that use Transactional Memory. Preordered transactions eliminate the root cause of nondeterminism in transactional execution: they provide the illusion of executing in a deterministic serial order, unlike traditional transactions that appear to execute in a nondeterministic order that can change from execution to execution. Pot uses a new concurrency control protocol that exploits the serialization order to distinguish between fast and speculative transaction execution modes in order to mitigate the overhead of imposing a deterministic order. We build two Pot prototypes: one using STM and another using off-the-shelf HTM. To the best of our knowledge, Pot enables deterministic execution of programs using off-the-shelf HTM for the first time. An experimental evaluation shows that Pot achieves deterministic execution of TM programs with low overhead, sometimes even outperforming nondeterministic executions, and clearly outperforming the state of the art.

SUMMARY Software transactional memory (STM) algorithms associate metadata with the memory locations accessed during a transaction's lifetime. This metadata may be stored in an external table by resorting to a mapping function that associates the address of a memory cell with the table entry containing the corresponding metadata (out‐place or external strategy). Alternatively, the metadata may be stored adjacent to the associated memory cell by wrapping the cell and metadata together (in‐place strategy). The implementation techniques to support these two approaches are very different and each STM framework is usually biased towards one of them, only allowing the efficient implementation of STM algorithms which suit one of the approaches and inhibiting a fair comparison with STM algorithms suiting the other. In this paper, we introduce a technique to implement in‐place metadata that does not wrap memory cells, thus overcoming the bias and allowing STM algorithms to directly access the transactional metadata. The proposed technique is available as an extension to Deuce and enables the efficient implementation of a wide range of STM algorithms and their fair (unbiased) comparison in a common STM framework. We illustrate the benefits of our approach by analyzing its impact in two popular transactional memory algorithms with several transactional workloads, TL2 and multiversioning, each befitting out‐place and in‐place, respectively. Copyright © 2013 John Wiley & Sons, Ltd.