Towards automatic construction of staged compilers

  • Authors:

  • Matthai Philipose;Craig Chambers;Susan J. Eggers

  • Affiliations:

  • University of Washington, Seattle WA;University of Washington, Seattle WA;University of Washington, Seattle WA

  • Venue:
  • POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
  • Year:
  • 2002

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Abstract

Some compilation systems, such as offline partial evaluators and selective dynamic compilation systems, support staged optimizations. A staged optimization is one where a logically single optimization is broken up into stages, with the early stage(s) performing preplanning set-up work, given any available partial knowledge about the program to be compiled, and the final stage completing the optimization. The final stage can be much faster than the original optimization by having much of its work performed by the early stages. A key limitation of current staged optimizers is that they are written by hand, sometimes in an ad hoc manner. We have developed a framework called the Staged Compilation Framework (SCF) for systematically and automatically converting single-stage optimizations into staged versions. The framework is based on a combination of aggressive partial evaluation and dead-assignment elimination. We have implemented SCF in Standard ML. A preliminary evaluation shows that SCF can speed up classical optimization of some commonly used C functions by up to 12× (and typically between 4.5× and 5.5×).