Partial Cross-Compilation and Mixed Execution for Accelerating Dynamic Binary Translation
Yuhao Gu, Zhongchun Zheng, Nong Xiao, Yutong Lu, Xianwei Zhang
TL;DR
The paper tackles the slowdown of cross-ISA execution by introducing TECH-NAME, a hybrid mechanism that offloads selected guest functions to native host code to bypass dynamic binary translation overhead. It integrates compile-time function extraction with runtime bridging to manage ABI differences and interleaved host-guest calls, supported by optimizations (GRT, FCP, PFO) to minimize cross-boundary costs. A practical prototype, IMPL-NAME, built on LLVM and QEMU, demonstrates substantial speedups (up to ~13x on AArch64 and ~19x on x86-64; mean ~3x) and shows applicability to libraries as well as applications. The work demonstrates the practical potential of automated, source-guided offloading for broad real-world software, including legacy and closed-source components, and points to future improvements in adaptive offloading and deeper compiler-emulator co-optimizations.
Abstract
With the growing diversity of instruction set architectures (ISAs), cross-ISA program execution has become common. Dynamic binary translation (DBT) is the main solution but suffers from poor performance. Cross-compilation avoids emulation costs but is constrained by an "all-or-nothing" model-programs are either fully cross-compiled or entirely emulated. Complete cross-compilation is often unfeasible due to ISA-specific code or missing dependencies, leaving programs with high emulation overhead. We propose a hybrid execution system that combines compilation and emulation, featuring a selective function offloading mechanism. This mechanism establishes cross-environment calling channels, offloading eligible functions to the host for native execution to reduce DBT overhead. Key optimizations address offloading costs, enabling efficient hybrid operation. Built on LLVM and QEMU, the system works automatically for both applications and libraries. Evaluations show it achieves up to 13x speedups over existing DBT, with strong practical value.
