71 research outputs found

    Analysis, classification and comparison of scheduling techniques for software transactional memories

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    Transactional Memory (TM) is a practical programming paradigm for developing concurrent applications. Performance is a critical factor for TM implementations, and various studies demonstrated that specialised transaction/thread scheduling support is essential for implementing performance-effective TM systems. After one decade of research, this article reviews the wide variety of scheduling techniques proposed for Software Transactional Memories. Based on peculiarities and differences of the adopted scheduling strategies, we propose a classification of the existing techniques, and we discuss the specific characteristics of each technique. Also, we analyse the results of previous evaluation and comparison studies, and we present the results of a new experimental study encompassing techniques based on different scheduling strategies. Finally, we identify potential strengths and weaknesses of the different techniques, as well as the issues that require to be further investigated

    Adaptive Transactional Memories: Performance and Energy Consumption Tradeoffs

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    Energy efficiency is becoming a pressing issue, especially in large data centers where it entails, at the same time, a non-negligible management cost, an enhancement of hardware fault probability, and a significant environmental footprint. In this paper, we study how Software Transactional Memories (STM) can provide benefits on both power saving and the overall applications’ execution performance. This is related to the fact that encapsulating shared-data accesses within transactions gives the freedom to the STM middleware to both ensure consistency and reduce the actual data contention, the latter having been shown to affect the overall power needed to complete the application’s execution. We have selected a set of self-adaptive extensions to existing STM middlewares (namely, TinySTM and R-STM) to prove how self-adapting computation can capture the actual degree of parallelism and/or logical contention on shared data in a better way, enhancing even more the intrinsic benefits provided by STM. Of course, this benefit comes at a cost, which is the actual execution time required by the proposed approaches to precisely tune the execution parameters for reducing power consumption and enhancing execution performance. Nevertheless, the results hereby provided show that adaptivity is a strictly necessary requirement to reduce energy consumption in STM systems: Without it, it is not possible to reach any acceptable level of energy efficiency at all

    A speculative execution approach to provide semantically aware contention management for concurrent systems

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    PhD ThesisMost modern platforms offer ample potention for parallel execution of concurrent programs yet concurrency control is required to exploit parallelism while maintaining program correctness. Pessimistic con- currency control featuring blocking synchronization and mutual ex- clusion, has given way to transactional memory, which allows the composition of concurrent code in a manner more intuitive for the application programmer. An important component in any transactional memory technique however is the policy for resolving conflicts on shared data, commonly referred to as the contention management policy. In this thesis, a Universal Construction is described which provides contention management for software transactional memory. The technique differs from existing approaches given that multiple execution paths are explored speculatively and in parallel. In the resolution of conflicts by state space exploration, we demonstrate that both concur- rent conflicts and semantic conflicts can be solved, promoting multi- threaded program progression. We de ne a model of computation called Many Systems, which defines the execution of concurrent threads as a state space management problem. An implementation is then presented based on concepts from the model, and we extend the implementation to incorporate nested transactions. Results are provided which compare the performance of our approach with an established contention management policy, under varying degrees of concurrent and semantic conflicts. Finally, we provide performance results from a number of search strategies, when nested transactions are introduced

    Extending Transactional Memory with Atomic Deferral

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    This paper introduces atomic deferral, an extension to TM that allows programmers to move long-running or irrevocable operations out of a transaction while maintaining serializability: the transaction and its de- ferred operation appear to execute atomically from the perspective of other transactions. Thus, program- mers can adapt lock-based programs to exploit TM with relatively little effort and without sacrificing scalability by atomically deferring the problematic operations. We demonstrate this with several use cases for atomic deferral, as well as an in-depth analysis of its use on the PARSEC dedup benchmark, where we show that atomic deferral enables TM to be competitive with well-designed lock-based code

    08241 Abstracts Collection -- Transactional Memory : From Implementation to Application

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    From 08.06. to 13.06.2008, the Dagstuhl Seminar 08241 ``Transactional Memory: From Implementation to Application\u27\u27 was held in Schloss Dagstuhl -- Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    Adaptive software transactional memory : dynamic contention management

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    This thesis addresses the problem of contention management in Software Transactional Memory (STM), which is a scheme for managing shared memory in a concurrent programming environment. STM views shared memory in a way similar to that of a database; read and write operations are handled through transactions, with changes to the shared memory becoming permanent through commit operations. Research on this subject reveals that there are currently varying methods for collision detection, data validation, and contention management, each of which has different situations in which they become the preferred method. This thesis introduces a dynamic contention manager that monitors current performance and chooses the proper contention manager accordingly. Performance calculations, and subsequent polling of the underlying library, are minimized. As a result, this adaptive contention manager yields a higher average performance level over time when compared with existing static implementations

    Tailoring Transactional Memory to Real-World Applications

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    Transactional Memory (TM) promises to provide a scalable mechanism for synchronizationin concurrent programs, and to offer ease-of-use benefits to programmers. Since multiprocessorarchitectures have dominated CPU design, exploiting parallelism in program

    Adaptive transaction scheduling for transactional memory systems

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    Transactional memory systems are expected to enable parallel programming at lower programming complexity, while delivering improved performance over traditional lock-based systems. Nonetheless, there are certain situations where transactional memory systems could actually perform worse. Transactional memory systems can outperform locks only when the executing workloads contain sufficient parallelism. When the workload lacks inherent parallelism, launching excessive transactions can adversely degrade performance. These situations will actually become dominant in future workloads when large-scale transactions are frequently executed. In this thesis, we propose a new paradigm called adaptive transaction scheduling to address this issue. Based on the parallelism feedback from applications, our adaptive transaction scheduler dynamically dispatches and controls the number of concurrently executing transactions. In our case study, we show that our low-cost mechanism not only guarantees that hardware transactional memory systems perform no worse than a single global lock, but also significantly improves performance for both hardware and software transactional memory systems.M.S.Committee Chair: Lee, Hsien-Hsin; Committee Member: Blough, Douglas; Committee Member: Yalamanchili, Sudhaka
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