Unleashing the Power of Learning: An Enhanced Learning-Based Approach for Dynamic Binary Translation


Changheng Song, Fudan University; Wenwen Wang, Pen-Chung Yew, and Antonia Zhai, University of Minnesota; Weihua Zhang, Fudan University


Dynamic binary translation (DBT) is a key system technology that enables many important system applications such as system virtualization and emulation. To achieve good performance, it is important for a DBT system to be equipped with high-quality translation rules. However, most translation rules in existing DBT systems are created manually with high engineering efforts and poor quality. To solve this problem, a learning-based approach was recently proposed to automatically learn semantically-equivalent translation rules, and symbolic verification is used to prove the semantic equivalence of such rules. But, they still suffer from some shortcomings.

In this paper, we first give an in-depth analysis on the constraints of prior learning-based methods and observe that the equivalence requirements are often unduly restrictive. It excludes many potentially high-quality rule candidates from being included and applied. Based on this observation, we propose an enhanced learning-based approach that relaxes such equivalence requirements but supplements them with constraining conditions to make them semantically equivalent when such rules are applied. Experimental results on SPEC CINT2006 show that the proposed approach can improve the dynamic coverage of the translation from 55.7% to 69.1% and the static coverage from 52.2% to 61.8%, compared to the original approach. Moreover, up to 1.65X performance speedup with an average of 1.19X are observed.

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@inproceedings {234972,
author = {Changheng Song and Wenwen Wang and Pen-Chung Yew and Antonia Zhai and Weihua Zhang},
title = {Unleashing the Power of Learning: An Enhanced {Learning-Based} Approach for Dynamic Binary Translation},
booktitle = {2019 USENIX Annual Technical Conference (USENIX ATC 19)},
year = {2019},
isbn = {978-1-939133-03-8},
address = {Renton, WA},
pages = {77--90},
url = {https://www.usenix.org/conference/atc19/presentation/song},
publisher = {USENIX Association},
month = jul

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