15/11/2020

Dataflow-Based Pruning for Speeding up Superoptimization

Manasij Mukherjee, Pranav Kant, Zhengyang Liu, John Regehr

Keywords: program synthesis, superoptimization, abstract interpretation, pruning

Abstract: Superoptimization is a compilation strategy that uses search to improve code quality, rather than relying on a canned sequence of transformations, as traditional optimizing compilers do. This search can be seen as a program synthesis problem: from unoptimized code serving as a specification, the synthesis procedure attempts to create a more efficient implementation. An important family of synthesis algorithms works by enumerating candidates and then successively checking if each refines the specification, using an SMT solver. The contribution of this paper is a pruning technique which reduces the enumerative search space using fast dataflow-based techniques to discard synthesis candidates that contain symbolic constants and uninstantiated instructions. We demonstrate the effectiveness of this technique by improving the runtime of an enumerative synthesis procedure in the Souper superoptimizer for the LLVM intermediate representation. The techniques presented in this paper eliminate 65

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