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Symbiotic Expressions

  • Robert Bernecky
  • Stephan Herhut
  • Sven-Bodo Scholz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6041)

Abstract

We introduce symbiotic expressions, a method for algebraic simplification within a compiler, in lieu of an SMT solver, such as Yices or the Omega Calculator. Symbiotic expressions are compiler-generated expressions, temporarily injected into a program’s abstract syntax tree (AST). The compiler’s normal optimizations interpret and simplify those expressions, making their results available for the compiler to use as a basis for decisions about further optimization of the source program. The expressions are symbiotic, in the sense that both parties benefit: an optimization benefits, by using the compiler itself to simplify expressions that have been attached, lamprey-like, to the AST by the optimization; the program being compiled benefits, from improved run-time in both serial and parallel environments.

We show the utility of symbiotic expressions by using them to extend the SAC compiler’s With-Loop-Folding optimization, currently limited to Arrays of Known Shape (AKS), to Arrays of Known Dimensionality (AKD). We show that, in conjunction with array-based constant-folding, injection and propagation of array extrema, and compiler-based expression simplification, symbiotic expressions are an effective tool for implementing advanced array optimizations. Symbiotic expressions are also simpler and more likely to be correct than hard-coded analysis, and are flexible and relatively easy to use. Finally, symbiotic expressions are synergistic: they take immediate advantage of new or improved optimizations in the compiler. Symbiotic expressions are a useful addition to a compiler writer’s toolkit, giving the compiler a restricted subset of the analysis power of an SMT solver.

Keywords

Index Vector Primitive Function Abstract Syntax Tree Cache Performance Intermediate Language 
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 2010

Authors and Affiliations

  • Robert Bernecky
    • 1
  • Stephan Herhut
    • 2
  • Sven-Bodo Scholz
    • 2
  1. 1.Snake Island Research IncTorontoCanada
  2. 2.University of HertfordshireU.K.

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