Data partitioning for maximal scratchpad usage

  • Authors:
  • Manish Verma;Stefan Steinke;Peter Marwedel

  • Affiliations:
  • University of Dortmund, Dortmund, Germany;University of Dortmund, Dortmund, Germany;University of Dortmund, Dortmund, Germany

  • Venue:
  • ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
  • Year:
  • 2003

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Abstract

The energy consumption for Mobile Embedded Systems is a limiting factor because of today's battery capacities. The memory subsystem consumes a large chunk of the energy, necessitating its efficient utilization. Energy efficient scratchpads are thus becoming common, though unlike caches they require to be explicitly utilized. In this paper, an algorithm integrated into a compiler is presented which analyzes the application, partitions an array variable whenever its beneficial, appropriately modifies the application and selects the best set of variables and program parts to be placed onto the scratchpad. Results show an energy improvement between 5.7% and 17.6% for a variety of applications against a previously known algorithm.