Accelerating Iterators in Optimizing AST Interpreters
Generators offer an elegant way to express iterators. However, their performance has always been their Achilles heel and has prevented widespread adoption. We present techniques to efficiently implement and optimize generators.
We have implemented our optimizations in ZipPy, a modern, light-weight AST interpreter based Python 3 implementation targeting the Java virtual machine. Our implementation builds on a framework that optimizes AST interpreters using just-in-time compilation. In such a system, it is crucial that AST optimizations do not prevent subsequent optimizations. Our system was carefully designed to avoid this problem. We report an average speedup of 3.58X for generator-bound programs. As a result, using generators no longer has downsides and programmers are free to enjoy their benefits.
Fri 24 OctDisplayed time zone: Tijuana, Baja California change
10:30 - 12:00
Dynamic OptimizationOOPSLA at Salon F
Chair(s): Zachary Tatlock University of Washington, Seattle
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Wei Zhang University of California, Irvine, Per Larsen University of California, Irvine, Stefan Brunthaler University of California, Irvine, Michael Franz University of California, IrvineLink to publication
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