Computation and communication refinement for multiprocessor SoC design: A system-level perspective
Proceedings of the 41st annual Design Automation Conference
SAPP: scalable and adaptable peak power management in nocs
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
PowerAntz: distributed power sharing strategy for network on chip
Proceedings of the 13th international symposium on Low power electronics and design
A distributed concurrent on-line test scheduling protocol for many-core NoC-based systems
ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
An overview of achieving energy efficiency in on-chip networks
International Journal of Communication Networks and Distributed Systems
Coordinating processor and main memory for efficientserver power control
Proceedings of the international conference on Supercomputing
A survey on techniques for improving the energy efficiency of large-scale distributed systems
ACM Computing Surveys (CSUR)
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As interconnection networks proliferate to a wide range of high-performance systems, power consumption is becoming a significant architectural issue. In interconnection networks, the peak-power consumption directly affects the solution for package cooling and power-delivery design. Off-line worst-case power analysis is typically used to estimate the network peak-power consumption and guarantee safe online operation, which not only increases system cost, but also constrains network performance. In this paper, we present an online mechanism, called PowerHerd, to efficiently manage network power resources at runtime, and guarantee that network peak-power constraints are not exceeded. PowerHerd is a distributed approach-within the interconnection network, each router dynamically maintains a local power budget, controls its local power dissipation, and exchanges spare power resources with its neighboring routers to optimize network performance. Experiments demonstrate that PowerHerd can effectively regulate network power consumption, meeting peak-power constraints with negligible network-performance penalty. Armed with PowerHerd, network designers can focus on system performance and power optimization for the average case, rather than the worst-case, thus making it possible to employ a more powerful interconnection network in the system.