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Instruction Selection for ARM/Thumb Processors Based on a Multi-objective Ant Algorithm

  • Shengning Wu
  • Sikun Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3967)

Abstract

In the embedded domain, not only performance, but also memory and energy are important concerns. A dual instruction set ARM processor, which supports a reduced Thumb instruction set with a smaller instruction length in addition to a full instruction set, provides an opportunity for a flexible tradeoff between these requirements. For a given program, typically the Thumb code is smaller than the ARM code, but slower than the latter, because a program compiled into the Thumb instruction set executes a larger number of instructions than the same program compiled into the ARM instruction set. Motivated by this observation, we propose a new Multi-objective Ant Colony Optimization (MOACO) algorithm that can be used to enable a flexible tradeoff between the code size and execution time of a program by using the two instruction sets selectively for different parts of a program. Our proposed approach determines the instruction set to be used for each function using a subset selection technique, and the execution time is the total one based on the profiling analyses of the dynamic behavior of a program. The experimental results show that our proposed technique can be effectively used to make the tradeoff between a program’s code size and execution time and can provide much flexibility in code generation for dual instruction set processors in general.

Keywords

Execution Time Code Size Benchmark Program State Transition Rule Instruction Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shengning Wu
    • 1
  • Sikun Li
    • 1
  1. 1.School of Computer ScienceNational University of Defense TechnologyChangshaChina

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