Enhancing Cross-ISA DBT Through Automatically Learned Translation Rules

Author:

Wang Wenwen1,McCamant Stephen1,Zhai Antonia1,Yew Pen-Chung1

Affiliation:

1. University of Minnesota, Twin Cities, Minneapolis, MN, USA

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 show that 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 short-running workloads.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Reference35 articles.

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