Risotto : a dynamic binary translator for weak memory model architectures

Dynamic Binary Translation (DBT) is a powerful approach to support cross-architecture emulation of unmodified binaries. However, DBT systems face correctness and performance challenges, when emulating concurrent binaries from strong to weak memory consistency architectures. As a matter of fact, we report several translation errors in Qemu, when emulating x86 binaries on Arm hosts. To address these challenges, we propose an end-to-end approach that provides correct and efficient emulation for weak memory model architectures. Our contributions are twofold: First, we formalize Qemu’s intermediate representation’s memory model, and use it to propose formally verified mapping schemes to bridge the strong-on-weak memory consistency mismatch. Second, we implement these verified mappings in Risotto, a Qemu-based DBT system that optimizes memory fence placement while ensuring correctness. Risotto further improves performance via cross-architecture dynamic linking of native shared libraries and faster yet correct translation of compare-and-swap operations. We evaluate Risotto using multi-threaded benchmark suites and real-world applications, and show that Risotto improves the emulation performance by 6.7% on average over “erroneous” Qemu, while ensuring correctness.Postprin