Profiling and Optimizing Transactional Memory Applications

Abstract

Many researchers have developed applications using transactional memory (TM) with the purpose of benchmarking different implementations, and studying whether or not TM is easy to use. However, comparatively little has been done to provide general-purpose tools for profiling and optimizing programs which use transactions. In this paper we introduce a series of profiling and optimization techniques for 123 26 Int J Parallel Prog (2012) 40:25-56 TM applications. The profiling techniques are of three types: (i) techniques to identify multiple potential conflicts from a single program run, (ii) techniques to identify the data structures involved in conflicts by using a symbolic path through the heap, rather than a machine address, and (iii) visualization techniques to summarize how threads spend their time and which of their transactions conflict most frequently. Altogether they provide in-depth and comprehensive information about the wasted work caused by aborting transactions. To reduce the contention between transactions we suggest several TM specific optimizations which leverage nested transactions, transaction checkpoints, early release and etc. To examine the effectiveness of the profiling and optimization techniques, we provide a series of illustrations from the STAMP TM benchmark suite and from the synthetic WormBench workload. First we analyze the performance of TM applications using our profiling techniques and then we apply various optimizations to improve the performance of the Bayes, Labyrinth and Intruder applications. We discuss the design and implementation of the profiling techniques in the Bartok-STM system. We process data offline or during garbage collection, where possible, in order to minimize the probe effect introduced by profiling.

Shared-Memory Synchronization

“…Zyulkyarov et al [2011Zyulkyarov et al [ , 2010 propose to differentiate, explicitly, between debugging an application, debugging the code inside atomic blocks, and debugging the TM implementation. e most obvious issue for debugging is the tension between the desire on the one hand to support debugging at the level of statements or machine instructions and, on the other hand, the need for transactions to effect their memory updates as a single indivisible operation.…”

Profile-guided transaction coalescing—lowering transactional overheads by merging transactions

“…This model could be used to analyze the benefits of transaction coalescing even before the program is executed. Zyulkyarov et al [2012] introduce transaction profiling techniques to identify multiple potential conflicts from a single program run and the data structures involved in conflicts. Their techniques could be used to eliminate highly conflicting transactions from the candidates for coalescing.…”