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HPCA2020顶会

DRAIN: Deadlock Removal for Arbitrary Irregular Networks

Mayank Parasar, Hossein Farrokhbakht, Natalie D. Enright Jerger, Paul V. Gratz, Tushar Krishna, Joshua San Miguel

2020年份
34被引次数
4顶会引用

摘要

Correctness is a first-order concern in the design of computer systems. For multiprocessors, a primary correctness concern is the deadlock-free operation of the network and its coherence protocol; furthermore, we must guarantee the continued correctness of the network in the face of increasing faults. Designing for deadlock freedom is expensive. Prior solutions either sacrifice performance or power efficiency to proactively avoid deadlocks or impose high hardware complexity to reactively resolve deadlocks as they occur. However, the precise confluence of events that lead to deadlocks is so rare that minimal resources and time should be spent to ensure deadlock freedom. To that end, we propose DRAIN, a subactive approach to remove potential deadlocks without needing to explicitly detect or avoid them. We simply let deadlocks happen and periodically drain (i.e., force the movement of) packets in the network that may be involved in a cyclic dependency. As deadlocks are a rare occurrence, draining can be performed infrequently and at low cost. Unlike prior solutions, DRAIN eliminates not only routing-level but also protocol-level deadlocks without the need for expensive virtual networks. DRAIN dramatically simplifies deadlock freedom for irregular topologies and networks that are prone to wear-related faults. Our evaluations show that on an average, DRAIN can save 26.73% packet latency compared to proactive deadlock-freedom schemes in the presence of faults while saving 77.6% power compared to reactive schemes.

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