SPLASH 2022
Mon 5 - Sat 10 December 2022 Auckland, New Zealand
Wed 7 Dec 2022 16:00 - 16:30 at AMRF Auditorium - DLS Talks 2 Chair(s): James Noble

Applications written in dynamic languages are becoming larger and larger and companies increasingly use multi-million line codebases in production. At the same time, dynamic languages rely heavily on dynamic optimizations, particularly those that reduce the overhead of method calls.

In this work, we study the call-site behavior of Ruby benchmarks that are being used to guide the development of upcoming Ruby implementations such as TruffleRuby and YJIT. We study the interaction of call-site lookup caches, method splitting, and elimination of duplicate call-targets.

We find that these optimizations are indeed highly effective on both smaller and large benchmarks, methods and closures alike, and help to open up opportunities for further optimizations such as inlining. However, we show that TruffleRuby’s splitting may be applied too aggressively on already-monomorphic call-sites, coming at a run-time cost. We also find three distinct patterns in the evolution of call-site behavior over time, which may help to guide novel optimizations. We believe that our results may support language implementers in optimizing runtime systems for large codebases built in dynamic languages.

Wed 7 Dec

Displayed time zone: Auckland, Wellington change

15:30 - 17:00
DLS Talks 2DLS at AMRF Auditorium
Chair(s): James Noble Research & Programming
15:30
30m
Talk
Execution vs. Parse-Based Language Servers: Tradeoffs and Opportunities for Language-Agnostic Tooling for Dynamic Languages
DLS
Stefan Marr University of Kent, Humphrey Burchell University of Kent, Fabio Niephaus Oracle Labs, Potsdam
DOI Pre-print
16:00
30m
Talk
Who You Gonna Call: Analyzing the Run-time Call-Site Behavior of Ruby Applications
DLS
Sophie Kaleba University of Kent, Octave Larose University of Kent, Richard Jones University of Kent, Stefan Marr University of Kent
DOI Pre-print
16:30
30m
Talk
Dynamic Pattern Matching with Python
DLS
Tobias Kohn University of Cambridge, UK, Guido van Rossum Python Software Foundation, Gary Brandt Bucher, II Research Affiliates, LLC, Talin , Ivan Levkivskyi Dropbox Ireland
DOI Pre-print
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