Multi-objective mapping for mesh-based NoC architectures

ABSTRACT

In this paper we present an approach to multi-objective exploration of the mapping space of a mesh-based network-on-chip architecture. Based on evolutionary computing techniques, the approach is an efficient and accurate way to obtain the Pareto mappings that optimize performance and power consumption. Integration of the approach in an exploration framework with a kernel based on an event-driven trace-based simulator makes it possible to take account of important dynamic effects that have a great impact on mapping. Validation on both synthesized traffic and real applications (an MPEG-2 encoder/decoder system) confirms the efficiency, accuracy and scalability of the approach.

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INDEX TERMS

Primary Classification:
  B. Hardware
  B.4 INPUT/OUTPUT AND DATA COMMUNICATIONS
      B.4.3 Interconnections (subsystems)

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.7 Simulation Support Systems
          Subjects: Environments

General Terms:
Design, Performance

Keywords:
genetic algorithms, mapping, multi-objective optimization, network-on-chip, simulation