Dr Wenowdis: Specializing dynamic language C extensions using type information
C-based interpreters such as CPython make extensive use of C “extension” code, which is opaque to static analysis tools and faster runtimes with JIT compilers, such as PyPy. Not only are the extensions opaque, but the interface between the dynamic language types and the C types can introduce impedance. We hypothesise that frequent calls to C extension code introduce significant overhead that is often unnecessary.
We validate this hypothesis by introducing a simple technique, “typed methods”, which allow selected C extension functions to have additional metadata attached to them in a backward-compatible way. This additional metadata makes it much easier for a JIT compiler (and as we show, even an interpreter!) to significantly reduce the call and return overhead.
Although we have prototyped typed methods in PyPy, we suspect that the same technique is applicable to a wider variety of language runtimes and that the information can also be consumed by static analysis tooling.
Dr Wenowdis (slides) (dr-wenowdis-slides.pdf) | 1007KiB |
Tue 25 JunDisplayed time zone: Windhoek change
10:40 - 12:20 | |||
10:40 50mKeynote | Challenges and Opportunities in Program Analysis for JavaScript SOAP Anders Møller Aarhus University | ||
11:30 20mTalk | Dr Wenowdis: Specializing dynamic language C extensions using type information SOAP Pre-print File Attached | ||
11:50 20mTalk | Interleaving Static Analysis and LLM Prompting SOAP Patrick Chapman University of California, Davis, Cindy Rubio-González University of California at Davis, Aditya V. Thakur University of California at Davis |