通过自动学习翻译规则增强跨isa DBT

Wenwen Wang, Stephen McCamant, Antonia Zhai, P. Yew
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引用次数: 16

摘要

本文提出了一种动态二进制翻译(DBT)的新方法,该方法可以从从相同源代码编译的来宾和主机二进制文件中自动学习翻译规则。然后通过二进制符号执行验证学习到的翻译规则,并在现有的DBT系统QEMU中使用,以生成更高效的主机二进制代码。在SPEC CINT2006上的实验结果表明,学习一条翻译规则的平均时间小于2秒。通过从一系列基准测试程序(不包括目标程序本身)中学习到的规则,SPEC CINT2006可以实现比QEMU平均1.25倍的性能加速。此外,即使对于短时间运行的工作负载,这种基于规则的方法引入的转换开销也非常小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Cross-ISA DBT Through Automatically Learned Translation Rules
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.
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