PowerHerd: A distributed scheme for dynamically satisfying peak-power constraints in interconnection networks

Li Shang, Li Shiuan Peh, N. K. Jha

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)92-110
Number of pages19
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Issue number1
StatePublished - Jan 2006
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


  • Interconnection networks
  • Local power budget
  • Local power dissipation
  • Network peak-power consumption
  • Network power resource management
  • Network-performance penalty
  • Package cooling
  • Power optimization
  • Power-delivery design
  • PowerHerd
  • System performance


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