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Staring into the Abyss: An Evaluation of Concurrency Control with One Thousand Cores

机译:盯着深渊:用一千个核心评估并发控制

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Computer architectures are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented level of on-chip parallelism introduces a new dimension to scalability that current database management systems (DBMSs) were not designed for. In particular, as the number of cores increases, the problem of concurrency control becomes extremely challenging. With hundreds of threads running in parallel, the complexity of coordinating competing accesses to data will likely diminish the gains from increased core counts. To better understand just how unprepared current DBMSs are for future CPU architectures, we performed an evaluation of concurrency control for on-line transaction processing (OLTP) workloads on many-core chips. We implemented seven concurrency control algorithms on a main-memory DBMS and using computer simulations scaled our system to 1024 cores. Our analysis shows that all algorithms fail to scale to this magnitude but for different reasons. In each case, we identify fundamental bottlenecks that are independent of the particular database implementation and argue that even state-of-the-art DBMSs suffer from these limitations. We conclude that rather than pursuing incremental solutions, many-core chips may require a completely redesigned DBMS architecture that is built from ground up and is tightly coupled with the hardware.
机译:计算机架构正在朝着由数十个甚至数百个芯片的多核机架主导的时代。这个前所未有的片上并行性引入了新的维度,以扩展性的可扩展性,即当前的数据库管理系统(DBMS)没有设计。特别是,随着核心的数量增加,并发控制的问题变得非常具有挑战性。随着数百个并行运行的线程,协调竞争访问对数据的复杂性可能会降低从增加的核心计数中的收益。为了更好地了解毫无准备的当前DBMS对于未来的CPU架构,我们对许多核心芯片上的在线事务处理(OLTP)工作负载进行了对并发控制的评估。我们在主内存DBM上实施了七种并发控制算法,并使用计算机模拟将我们的系统缩放到1024核心。我们的分析表明,所有算法都无法扩展到这种幅度,而是出于不同的原因。在每种情况下,我们识别独立于特定数据库实施的基本瓶颈,并争辩说甚至最先进的DBMS患有这些限制。我们得出结论,而不是追求增量解决方案,许多核心芯片可能需要完全重新设计的DBMS架构,该架构由接地构建并与硬件紧密耦合。

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