Building efficient and highly run-time adaptable virtual machines

Guido Chari, Diego Garbervetsky, Stefan Marr

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Programming language virtual machines (VMs) realize language semantics, enforce security properties, and execute applications efficiently. Fully Reflective Execution Environments (EEs) are VMs that additionally expose their whole structure and behavior to applications. This enables develop- ers to observe and adapt VMs at run time. However, there is a belief that reflective EEs are not viable for practical usages because such flexibility would incur a high performance overhead. To refute this belief, we built a reflective EE on top of a highly optimizing dynamic compiler. We introduced a new optimization model that, based on the conjecture that variability of low-level (EE-level) reflective behavior is low in many scenarios, mitigates the most significant sources of the performance overheads related to the reflective capabilities in the EE. Our experiments indicate that reflective EEs can reach peak performance in the order of standard VMs. Concretely, that a) if reflective mechanisms are not used the execution overhead is negligible compared to standard VMs, b) VM operations can be redefined at language-level without incurring in significant overheads, c) for several software adaptation tasks, applying the reflection at the VM level is not only lightweight in terms of engineering effort, but also competitive in terms of performance in comparison to other ad-hoc solutions.
Original languageEnglish
Title of host publicationProceeding DLS 2016 Proceedings of the 12th Symposium on Dynamic Languages
Place of PublicationNew York
PublisherACM
Pages60-71
Number of pages12
ISBN (Print)978-1-4503-4445-6
DOIs
Publication statusPublished - Nov 2016

Fields of science

  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102011 Formal languages
  • 102013 Human-computer interaction
  • 102022 Software development
  • 102024 Usability research
  • 102029 Practical computer science

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

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