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Efficient fault-tolerance for pipelined structures and its application to superscalar and dataflow machines.

机译:管道结构的高效容错及其在超标量和数据流机器中的应用。

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Silicon reliability has reemerged as a very important problem in digital system design. As voltage and device dimensions shrink, combinational logic is becoming sensitive to temporary errors caused by single event upsets, transistor and interconnect aging and circuit variability. In particular, computational functional units are very challenging to protect because current redundant execution techniques have a high power and area overhead, cannot guarantee detection of some errors and cause a substantial performance degradation. As traditional worst-case design rules that guarantee error avoidance become too conservative to be practical, new microarchitectures need to be investigated to address this problem.;To this end, this dissertation introduces Self-Imposed Temporal Redundancy (SITR), a speculative microarchitectural temporal redundancy technique suitable for pipelined computational functional units. SITR is able to detect most temporary errors, is area and energy-efficient and can be easily incorporated in an out-of-order microprocessor. SITR can also be used as a throttling mechanism against thermal viruses and, in some cases, allows designers to design very aggressive bypass networks capable of achieving high instruction throughput, by tolerating timing violations.;To address the performance degradation caused by redundant execution, this dissertation proposes using a tiled-dataflow model of computation because it enables the design of scalable, resource-rich computational substrates. Starting with the WaveScalar tiled-dataflow architecture, we enhance the reliability of its datapath, including computational logic, interconnection network and storage structures. Computations are performed speculatively using SITR while traditional information redundancy techniques are used to protect data transmission and storage. Once a value has been verified, confirmation messages are transmitted to consumer instructions. Upon error detection, nullification messages are sent to the instructions affected by the error.;Our experimental results demonstrate that the slowdown due to redundant computation and error recovery on the tiled-dataflow machine is consistently smaller than on a superscalar von Neumann architecture. However, the number of additional messages required to support SITR execution is substantial, increasing power consumption. To reduce this overhead without significantly affecting performance, we introduce wave-based speculation, a mechanism targeted for dataflow architectures that enables speculation only when it is likely to benefit performance.
机译:硅可靠性已经重新成为数字系统设计中的一个重要问题。随着电压和器件尺寸的缩小,组合逻辑对由单事件故障,晶体管和互连老化以及电路可变性引起的临时错误变得敏感。特别地,由于当前的冗余执行技术具有高功率和面积开销,不能保证检测到某些错误并导致性能大幅下降,因此保护功能非常困难。由于传统的保证避免错误的最坏情况设计规则变得过于保守而无法实际应用,因此需要研究新的微体系结构以解决此问题。为此,本文引入了自发性时间冗余(SITR),一种推测性微体系结构时态适用于流水线计算功能单元的冗余技术。 SITR能够检测到大多数临时错误,面积小且节能,并且可以轻松地集成到乱序的微处理器中。 SITR还可以用作针对热病毒的调节机制,在某些情况下,允许设计人员设计出非常激进的旁路网络,通过容许时序违规来实现高指令吞吐量。为了解决冗余执行导致的性能下降,这论文提出使用计算的平铺数据流模型,因为它能够设计可扩展的,资源丰富的计算基础。从WaveScalar切片数据流架构开始,我们增强了其数据路径的可靠性,包括计算逻辑,互连网络和存储结构。计算是使用SITR进行推测性执行的,而传统的信息冗余技术则用于保护数据的传输和存储。验证值后,确认消息将发送到消费者指令。检测到错误后,会将无效消息发送到受错误影响的指令。我们的实验结果表明,平铺数据流计算机上由于冗余计算和错误恢复而导致的速度始终小于超标量冯·诺依曼体系结构。但是,支持SITR执行所需的附加消息数量很大,从而增加了功耗。为了在不显着影响性能的情况下减少开销,我们引入了基于波动的推测,这是一种针对数据流体系结构的机制,仅在可能有益于性能的情况下才启用推测。

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