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首页> 外文期刊>International journal of parallel programming >Architectural Support for Fault Tolerance in a Teradevice Dataflow System
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Architectural Support for Fault Tolerance in a Teradevice Dataflow System

机译:Teradevice数据流系统中的容错的体系结构支持

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The high parallelism of future Teradevices, which are going to contain more than 1,000 complex cores on a single die, requests new execution paradigms. Coarsegrained dataflow execution models are able to exploit such parallelism, since they combine side-effect free execution and reduced synchronization overhead. However, the terascale transistor integration of such future chips make them orders of magnitude more vulnerable to voltage fluctuation, radiation, and process variations. This means dynamic fault-tolerance mechanisms have to be an essential part of such future system. In this paper, we present a fault tolerant architecture for a coarse-grained dataflow system, leveraging the inherent features of the dataflow execution model. In detail, we provide methods to dynamically detect and manage permanent, intermittent, and transient faults during runtime. Furthermore, we exploit the dataflow execution model for a thread-level recovery scheme. Our results showed that redundant execution of dataflow threads can efficiently make use of underutilized resources in a multi-core, while the overhead in a fully utilized system stays reasonable. Moreover, thread-level recovery suffered from moderate overhead, even in the case of high fault rates.
机译:未来Teradevices的高度并行性将在一个裸片上包含1,000多个复杂内核,因此需要新的执行范例。粗粒度的数据流执行模型能够利用这种并行性,因为它们结合了无副作用的执行和减少的同步开销。但是,这种未来芯片的万亿级晶体管集成度使其数量级更容易受到电压波动,辐射和工艺变化的影响。这意味着动态的容错机制必须成为此类未来系统的重要组成部分。在本文中,我们利用数据流执行模型的固有功能,提出了一种用于粗粒度数据流系统的容错体系结构。详细地说,我们提供了在运行时动态检测和管理永久性,间歇性和瞬态故障的方法。此外,我们将数据流执行模型用于线程级恢复方案。我们的结果表明,数据流线程的冗余执行可以有效地利用多核中未充分利用的资源,而充分利用的系统中的开销保持合理。此外,即使在高故障率的情况下,线程级恢复也要承受中等的开销。

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