Enhancing cross-ISA DBT through automatically learned translation rules

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents a novel approach for dynamic binary translation (DBT) to automatically learn translation rules from guest and host binaries compiled from the same source code. The learned translation rules are then verified via binary symbolic execution and used in an existing DBT system, QEMU, to generate more efficient host binary code. Experimental results on SPEC CINT2006 showthat the average time of learning a translation rule is less than two seconds. With the rules learned from a collection of benchmark programs excluding the targeted program itself, an average 1.25X performance speedup over QEMU can be achieved for SPEC CINT2006. Moreover, the translation overhead introduced by this rule-based approach is very small even for shortrunning workloads.

Original languageEnglish (US)
Title of host publicationASPLOS 2018 - 23rd International Conference on Architectural Support for Programming Languages and Operating Systems
PublisherAssociation for Computing Machinery
Pages84-97
Number of pages14
Volume53
Edition2
ISBN (Electronic)9781450349116
DOIs
StatePublished - Mar 19 2018
Event23rd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2018 - Williamsburg, United States
Duration: Mar 24 2018Mar 28 2018

Publication series

NameACM SIGPLAN Notices
PublisherAssociation for Computing Machinery (ACM)
ISSN (Print)1523-2867

Other

Other23rd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2018
Country/TerritoryUnited States
CityWilliamsburg
Period3/24/183/28/18

Bibliographical note

Funding Information:
We are very grateful to David Grove and the anonymous reviewers for their valuable comments and feedback. This material is based upon work supported by the National Science Foundation under Grant No. CNS-1514444. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Keywords

  • DBT
  • Rule learning
  • Symbolic execution

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