Should potential loop optimizations influence inlining decisions?

ABSTRACT

Inlining decisions are made based on the frequency of the function call, on the size of the caller and callee, on the nesting level of the function call in the call graph, and on the programmer's directives. In intraprocedural code optimization, loop fusion has proven to be advantageous when it results in improved data reuse, instruction scheduling, and register allocation. We want to study the opportunity to improve the performance of programs when the potential for additional loop fusion is taken into consideration in the inlining decisions. In this paper we present the results of our first evaluation experiments: we changed the inlining decisions in the IBM^®XL Compile Suite to inline liberally and measured how many additional loops we were able to fuse in the SPECint2000 and SPECfp2000 benchmark suites. The idea is that if liberal inlining does not result in significant additional loop fusion for a given set of benchmarks, there will be little hope for interprocedural loop fusion in that set. Our preliminary results indicate that existing inlining heuristics uncover almost all interprocedural loop fusion opportunities in the SPEC benchmark suite.

REFERENCES

• 1: Andrew Ayers , Richard Schooler , Robert Gottlieb, Aggressive inlining, Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation, p.134-145, June 16-18, 1997, Las Vegas, Nevada, United States
• 2: {2} Christopher Barton. Code transformations to augment the scope of loop fusion in a production compiler. Master's thesis, University of Alberta, January 2003.
• 3: {3} Bob Blainey, Christopher Barton, and Nelson Amaral. Removing impediments to loop fusion through code transformations. In Languages and Compilers for Parallel Computing, College Park, MD, July 2002.
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INDEX TERMS

Primary Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.4 Processors
          Subjects: Optimization

Additional Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.4 Processors
          Subjects: Compilers

General Terms:
Algorithms, Design, Experimentation, Performance