Unleashing the power of learning: An enhanced learning-based approach for dynamic binary translation

Changheng Song, Wenwen Wang, Pen Chung Yew, Antonia Zhai, Weihua Zhang

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

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 2019 USENIX Annual Technical Conference, USENIX ATC 2019
PublisherUSENIX Association
Pages77-89
Number of pages13
ISBN (Electronic)9781939133038
StatePublished - 2019
Event2019 USENIX Annual Technical Conference, USENIX ATC 2019 - Renton, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

NameProceedings of the 2019 USENIX Annual Technical Conference, USENIX ATC 2019

Conference

Conference2019 USENIX Annual Technical Conference, USENIX ATC 2019
CountryUnited States
CityRenton
Period7/10/197/12/19

Bibliographical note

Funding Information:
We are very grateful to our shepherd, Edouard Bugnion, and the anonymous reviewers for their valuable feedback and comments. This work is supported in part by the National Natural Science Foundation of China (No. 61672160), Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01) and ZJLab, Shanghai Sci-

Funding Information:
We are very grateful to our shepherd, Edouard Bugnion, and the anonymous reviewers for their valuable feedback and comments. This work is supported in part by the National Natural Science Foundation of China (No. 61672160), Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01) and ZJLab, Shanghai Science and Technology Development Funds (17511102200) and the National Science Foundation under the grant number CNS-1514444.

Funding Information:
ence and Technology Development Funds (17511102200) and the National Science Foundation under the grant number CNS-1514444.

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