Loop transformations for reducing data space requirements of resource-constrained applications

  • Authors:

  • Priya Unnikrishnan;Guangyu Chen;Mahmut Kandemir;Mustafa Karakoy;Ibrahim Kolcu

  • Affiliations:

  • CSE Department, Pennsylvania State University, University Park, PA;CSE Department, Pennsylvania State University, University Park, PA;CSE Department, Pennsylvania State University, University Park, PA;Department of Computing, Imperial College, London, UK;Computation Department, UMIST Manchester, UK

  • Venue:
  • SAS'03 Proceedings of the 10th international conference on Static analysis
  • Year:
  • 2003

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Abstract

Embedded computing platforms are often resource constrained, requiring great design and implementation attention to memory, power and heat related parameters. An important task for a compiler in such platforms is to simplify the process of developing applications for limited memory devices and resource constrained clients. Focusing on array-intensive embedded applications, this work explores how loop-based compiler optimizations can be used for increasing memory location reuse. Our goal is to transform a given application in such a way that the resulting code has fewer cases (as compared to the original code) where the lifetimes of array elements overlap. The reduction in lifetimes of array elements can then be exploited by reusing memory locations as much as possible. Our results indicate that the proposed strategy reduces data space requirements of ten resource constrained applications by more than 40% on the average.