10,774 research outputs found

    Programming Idioms for Transactional Events

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    Transactional events (TE) are an extension of Concurrent ML (CML), a programming model for synchronous message-passing. Prior work has focused on TE's formal semantics and its implementation. This paper considers programming idioms, particularly those that vary unexpectedly from the corresponding CML idioms. First, we solve a subtle problem with client-server protocols in TE. Second, we argue that CML's wrap and guard primitives do not translate well to TE, and we suggest useful workarounds. Finally, we discuss how to rewrite CML protocols that use abort actions

    Maintaining consistency in distributed systems

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    In systems designed as assemblies of independently developed components, concurrent access to data or data structures normally arises within individual programs, and is controlled using mutual exclusion constructs, such as semaphores and monitors. Where data is persistent and/or sets of operation are related to one another, transactions or linearizability may be more appropriate. Systems that incorporate cooperative styles of distributed execution often replicate or distribute data within groups of components. In these cases, group oriented consistency properties must be maintained, and tools based on the virtual synchrony execution model greatly simplify the task confronting an application developer. All three styles of distributed computing are likely to be seen in future systems - often, within the same application. This leads us to propose an integrated approach that permits applications that use virtual synchrony with concurrent objects that respect a linearizability constraint, and vice versa. Transactional subsystems are treated as a special case of linearizability

    Towards Efficient Abstractions for Concurrent Consensus

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    Consensus is an often occurring problem in concurrent and distributed programming. We present a programming language with simple semantics and build-in support for consensus in the form of communicating transactions. We motivate the need for such a construct with a characteristic example of generalized consensus which can be naturally encoded in our language. We then focus on the challenges in achieving an implementation that can efficiently run such programs. We setup an architecture to evaluate different implementation alternatives and use it to experimentally evaluate runtime heuristics. This is the basis for a research project on realistic programming language support for consensus.Comment: 15 pages, 5 figures, symposium: TFP 201

    Conjoined Events

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    Many existing synchronous message-passing systems support choice: engaging in one event XOR another. This paper introduces the AND operator that allows a process to engage in multiple events together (one AND one more AND another; all conjoined), engaging in each event only if it can atomically engage in all the conjoined events. We demonstrate using several examples that this operator supports new, more ?exible models of programming. We show that the AND operator allows the behaviour of processes to be expressed in local rules rather than system-wide constructs. We give an optimised implementation of the AND operator and explore the performance effect on standard communications of supporting this new operator

    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

    Model-Based Proactive Read-Validation in Transaction Processing Systems

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    Concurrency control protocols based on read-validation schemes allow transactions which are doomed to abort to still run until a subsequent validation check reveals them as invalid. These late aborts do not favor the reduction of wasted computation and can penalize performance. To counteract this problem, we present an analytical model that predicts the abort probability of transactions handled via read-validation schemes. Our goal is to determine what are the suited points-along a transaction lifetime-to carry out a validation check. This may lead to early aborting doomed transactions, thus saving CPU time. We show how to exploit the abort probability predictions returned by the model in combination with a threshold-based scheme to trigger read-validations. We also show how this approach can definitely improve performance-leading up to 14 % better turnaround-as demonstrated by some experiments carried out with a port of the TPC-C benchmark to Software Transactional Memory

    On the Impact of Memory Allocation on High-Performance Query Processing

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    Somewhat surprisingly, the behavior of analytical query engines is crucially affected by the dynamic memory allocator used. Memory allocators highly influence performance, scalability, memory efficiency and memory fairness to other processes. In this work, we provide the first comprehensive experimental analysis on the impact of memory allocation for high-performance query engines. We test five state-of-the-art dynamic memory allocators and discuss their strengths and weaknesses within our DBMS. The right allocator can increase the performance of TPC-DS (SF 100) by 2.7x on a 4-socket Intel Xeon server
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