Avalanche: an environment for design space exploration and optimization of low-power embedded systems

  • Authors:
  • Jörg Henkel;Yanbing Li

  • Affiliations:
  • NEC Laboratories America, Princeton, NJ;Synopsys, Mountainview, CA

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • Year:
  • 2002

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Abstract

Power estimation and optimization has become a key issue in embedded system design, especially in the rapidly growing market of mobile handheld computing, communication, internet devices that are driven by battery power. It is of paramount importance to estimate and optimize power of those systems during an early design stage at a high level of abstraction in order to efficiently explore the design space and to take full advantage of the related high optimization potential.In this paper, we present Avalanche, a prototyping framework that addresses the issues of power estimation and optimization for mixed hardware and software embedded systems. Avalanche is based on a generic embedded system architecture consisting of embedded CPU, custom hardware, and a memory hierarchy. For system-level power estimation, given various system parameters like cache sizes, cache policies, and bus width, etc., Avalanche is able to rapidly evaluate/estimate power and performance and thus facilitate comprehensive design space explorations. For system-level power optimization, Avalanche offers different modes reflecting various design scenarios: if no hardware/software partitioning or only partial partitioning has been conducted, Avalanche guides the designer in finding power-aware hard-ware/software partitioning; when a system has already been partitioned, Avalanche can optimize system parameters such as cache and memory size; if system parameters and partitioning are given, Avalanche applies additional optimizations for power including source-to-source compiler transformations.Avalanche has been deployed during the design phase of real-world applications including an MPEG II encoder in a set-top box design. Extensive design space explorations in terms of power and performance could be conducted within several hours and various optimization techniques led to power reductions of up to 94% withoul performance losses and only a slight increases in total chip size (i.e., transistor count).