Affiliation:
1. Indiana University, USA
2. King's College London, UK
Abstract
While gradual typing has proven itself attractive to programmers, many systems have avoided sound gradual typing due to the run time overhead of enforcement. In the context of sound gradual typing, both anecdotal and systematic evidence has suggested that run time costs are quite high, and often unacceptable, casting doubt on the viability of soundness as an approach.
We show that these overheads are not fundamental, and that with appropriate improvements,
just-in-time compilers can greatly reduce the overhead of sound gradual typing
. Our study takes benchmarks published in a recent paper on gradual typing performance in Typed Racket (Takikawa et al., POPL 2016) and evaluates them using a experimental tracing JIT compiler for Racket, called Pycket. On typical benchmarks, Pycket is able to eliminate more than 90% of the gradual typing overhead. While our current results are not the final word in optimizing gradual typing, we show that the situation is not dire, and where more work is needed.
Pycket's performance comes from several sources, which we detail and measure individually. First, we apply a sophisticated tracing JIT compiler and optimizer, automatically generated in Pycket using the RPython framework originally created for PyPy. Second, we focus our optimization efforts on the challenges posed by run time checks, implemented in Racket by
chaperones and impersonators
. We introduce representation improvements, including a novel use of
hidden classes
to optimize these data structures.
Funder
National Science Foundation
EPSRC Cooler
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,Software
Cited by
21 articles.
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1. Nominal Types for Erlang;Proceedings of the 23rd ACM SIGPLAN International Workshop on Erlang;2024-08-28
2. Space-Efficient Polymorphic Gradual Typing, Mostly Parametric;Proceedings of the ACM on Programming Languages;2024-06-20
3. Type-Based Gradual Typing Performance Optimization;Proceedings of the ACM on Programming Languages;2024-01-05
4. How Profilers Can Help Navigate Type Migration;Proceedings of the ACM on Programming Languages;2023-10-16
5. GTP Benchmarks for Gradual Typing Performance;Proceedings of the 2023 ACM Conference on Reproducibility and Replicability;2023-06-27