Statistical approach to networks-on-chip

Itamar Cohen, Ori Rottenstreich, Isaac Keslassy

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Chip multiprocessors (CMPs) combine increasingly many general-purpose processor cores on a single chip. These cores run several tasks with unpredictable communication needs, resulting in uncertain and often-changing traffic patterns. This unpredictability leads network-on-chip (NoC) designers to plan for the worst case traffic patterns, and significantly overprovision link capacities. In this paper, we provide NoC designers with an alternative statistical approach. We first present the traffic-load distribution plots (T-Plots), illustrating how much capacity overprovisioning is needed to service 90, 99, or 100 percent of all traffic patterns. We prove that in the general case, plotting T-Plots is #P-complete, and therefore extremely complex. We then show how to determine the exact mean and variance of the traffic load on any edge, and use these to provide Gaussian-based models for the T-Plots, as well as guaranteed performance bounds. We also explain how to practically approximate T-Plots using random-walk-based methods. Finally, we use T-Plots to reduce the network power consumption by providing an efficient capacity allocation algorithm with predictable performance guarantees.

Original languageEnglish
Article number5416678
Pages (from-to)748-761
Number of pages14
JournalIEEE Transactions on Computers
Issue number6
StatePublished - 2010
Externally publishedYes


  • Capacity allocation
  • Chip multiprocessors
  • Networks-on-chip
  • Traffic-load distribution plot


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