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Mon 19 Jun 2017 12:05 - 12:30 at Aula Master - Compiler Optimizations Chair(s): Uday Bondhugula

Peephole optimizations are a common source of compiler bugs. Compiler developers typically transform an incorrect peephole optimization into a valid one by strengthening the precondition. This process is challenging and tedious. This paper proposes, PInfer, a data-driven approach for inferring preconditions for peephole optimizations expressed in Alive. PInfer generates positive and negatives examples for an optimization, enumerates predicates on-demand, and learns a set of predicates that separate the positive and negative examples. PInfer repeats this process until it finds a precondition that ensures the validity of the optimization. PInfer reports both the weakest precondition and a set of succinct partial preconditions to the developer. The PInfer prototype successfully generates either the partial precondition or the weakest precondition for 164 out of 174 peephole optimizations in the Alive suite. It also generates preconditions that are weaker than LLVM’s precondition for 73 optimizations. We also demonstrate the applicability of this technique to generalize 54 concrete expression directed acyclic graphs generated by an LLVM IR-based super optimizer.

Mon 19 Jun
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10:50 - 12:30: PLDI Research Papers - Compiler Optimizations at Aula Master
Chair(s): Uday BondhugulaIndian Institute of Science
pldi-2017-papers10:50 - 11:15
Jonathan Lifflander, Sriram KrishnamoorthyPacific Northwest National Laboratories
pldi-2017-papers11:15 - 11:40
Olli Saarikivi, Margus VeanesMicrosoft Research, Todd Mytkowicz, Madan MusuvathiMicrosoft Research
pldi-2017-papers11:40 - 12:05
Yufei DingNorth Carolina State University, Lin NingNorth Carolina State University, Hui GuanNorth Carolina State University, Xipeng ShenNorth Carolina State University
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pldi-2017-papers12:05 - 12:30
David MenendezRutgers University, Santosh NagarakatteRutgers University, USA
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