Understanding the behavior of transactional memory applications

Lourenço, João; Dias, Ricardo; Luis, João Sousa; Rebelo, Miguel; Pessanha, Vasco

doi:10.1145/1639622.1639625

Cited by 11 publications

(9 citation statements)

References 6 publications

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“…However, few works have been done concerning tools to help the development using TM. That is the case of the proposals presented in [15] and [16].…”

Section: Related Workmentioning

confidence: 95%

“…They have chosen three applications from STAMP and an implementation of Lee's routing algorithm, investigating some relevant metrics to comprehend TM applications. Lourenço et al [16] have proposed a monitoring framework, which collects the transactional events into a log file as well as a tool to visualize the results. Their instrumentation mechanism is based on a API, so the user must insert the tracing function calls within applications source codes.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Analysis and Tracing of Applications Based on Software Transactional Memory on Multicore Architectures

Castro

Georgiev

Marangozova-Martin

et al. 2011

2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing

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International audienceTransactional Memory (TM) is a new programming paradigm that offers an alternative to traditional lock-based concurrency mechanisms. It offers a higher-level programming interface and promises to greatly simplify the development of correct concurrent applications on multicore architectures. However, simplicity often comes with an important performance deterioration and given the variety of TM implementations it is still a challenge to know what kind of applications can really take advantage of TM. In order to gain some insight on these issues, helping developers to understand and improve the performance of TM applications, we propose a generic approach for collecting and tracing relevant information about transactions. Our solution can be applied to different Software Transactional Memory (STM) libraries and applications as it does not modify neither the target application nor the STM library source codes. We show that the collected information can be helpful in order to comprehend the performance of TM applications

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“…However, few works have been done concerning tools to help the development using TM. That is the case of the proposals presented in [15] and [16].…”

Section: Related Workmentioning

confidence: 95%

Section: Related Workmentioning

confidence: 99%

Analysis and Tracing of Applications Based on Software Transactional Memory on Multicore Architectures

Castro

Georgiev

Marangozova-Martin

et al. 2011

2011 19th International Euromicro Conference on Parallel, Distributed and Network-Based Processing

View full text Add to dashboard Cite

show abstract

“…They selected 3 applications from the benchmarks STAMP and Lee-TM to investigate and comprehend TM applications. Lourenço et al [12] implemented a framework with low overhead, which collects transactional events and stores them in a log file. To evaluate the results, they implemented a tool to visualize the collected transactional information.…”

Section: Evaluating the Impact Of Transactionalmentioning

confidence: 99%

“…As discussed in [11], it is still challenging to know what kind of applications can really take advantage of TM. Finally, as identified by [12], it is essential to investigate the reasons why some TM applications present low performance and how to identify in advance which applications can benefit from this model.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Impact of Transactional Characteristics on the Performance of Transactional Memory Applications

Rui

Castro

Griebler

et al. 2014

2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing

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Transactional Memory (TM) is reputed by many researchers to be a promising solution to ease parallel programming on multicore processors. This model provides the scalability of fine-grained locking while avoiding common issues of traditional mechanisms, such as deadlocks. During these almost twenty years of research, several TM systems and benchmarks have been proposed. However, TM is not yet widely adopted by the scientific community to develop parallel applications due to unanswered questions in the literature, such as "how to identify if a parallel application can exploit TM to achieve better performance?" or "what are the reasons of poor performances of some TM applications?". In this work, we contribute to answer those questions through a comparative evaluation of a set of TM applications on four different stateof-the-art TM systems. Moreover, we identify some of the most important TM characteristics that impact directly the performance of TM applications. Our results can be useful to identify opportunities for optimizations.

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“…Independently from us, Lourenço et al [24] have developed a tool for visualizing transactions similar to the transaction visualizer that we describe in Sect. 2.4.…”

Section: Related Workmentioning

confidence: 99%

Profiling and Optimizing Transactional Memory Applications

Zyulkyarov

Stipic

Harris³

et al. 2011

Int J Parallel Prog

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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.

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Understanding the behavior of transactional memory applications

Cited by 11 publications

References 6 publications

Analysis and Tracing of Applications Based on Software Transactional Memory on Multicore Architectures

Analysis and Tracing of Applications Based on Software Transactional Memory on Multicore Architectures

Evaluating the Impact of Transactional Characteristics on the Performance of Transactional Memory Applications

Profiling and Optimizing Transactional Memory Applications

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