Efficient MMU Emulation in Case of Cross-ISA Dynamic Binary Translation

The emergence of Aarch64-based servers and user PCs has renewed the relevance of full-system cross-ISA emulation. Dynamic binary translation is a commonly used technique for executing program code compiled for one processor architecture on a CPU of a different architecture. However, to run an entire program or operating system on a different architecture, other components must be virtualized too. One critical requirement for full-system emulation is the emulation of the Memory Management Unit (MMU). This paper presents an efficient method for emulating the MMU of the AMD64 architecture on the Aarch64 architecture. Our approach leverages shadow page tables compatible with the Aarch64 MMU to utilize hardware-assisted address translation. The proposed implementation demonstrates significantly improved performance compared to software MMU emulation.

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Published
2024-12-11
DOI
https://doi.org/10.1109/ispras64596.2024.10899135
Primary Topic
Brain Tumor Detection and Classification
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article
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Efficient MMU Emulation in Case of Cross-ISA Dynamic Binary Translation

Dmitry Koltunov, A G Cheremnov, Кирилл Батузов, Sergey Rodzevich et al.
Brain Tumor Detection and Classification
article

Efficient MMU Emulation in Case of Cross-ISA Dynamic Binary Translation

Dmitry Koltunov, A G Cheremnov, Кирилл Батузов, Sergey Rodzevich, Ilya Shlyapin
article en

Abstract

The emergence of Aarch64-based servers and user PCs has renewed the relevance of full-system cross-ISA emulation. Dynamic binary translation is a commonly used technique for executing program code compiled for one processor architecture on a CPU of a different architecture. However, to run an entire program or operating system on a different architecture, other components must be virtualized too. One critical requirement for full-system emulation is the emulation of the Memory Management Unit (MMU). This paper presents an efficient method for emulating the MMU of the AMD64 architecture on the Aarch64 architecture. Our approach leverages shadow page tables compatible with the Aarch64 MMU to utilize hardware-assisted address translation. The proposed implementation demonstrates significantly improved performance compared to software MMU emulation.

Institute for System Programming (RU)
Openalex Percentile: Top 68%
Brain Tumor Detection and Classification
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