ARMv8-A System Semantics: Instruction Fetch in Relaxed Architectures

AbstractComputing relies on architecture specifications to decouple hardware and software development. Historically these have been prose documents, with all the problems that entails, but research over the last ten years has developed rigorous and executable-as-test-oracle specifications of mainstream architecture instruction sets and “user-mode” concurrency, clarifying architectures and bringing them into the scope of programming-language semantics and verification. However, the system semantics, of instruction-fetch and cache maintenance, exceptions and interrupts, and address translation, remains obscure, leaving us without a solid foundation for verification of security-critical systems software.In this paper we establish a robust model for one aspect of system semantics: instruction fetch and cache maintenance for ARMv8-A. Systems code relies on executing instructions that were written by data writes, e.g. in program loading, dynamic linking, JIT compilation, debugging, and OS configuration, but hardware implementations are often highly optimised, e.g. with instruction caches, linefill buffers, out-of-order fetching, branch prediction, and instruction prefetching, which can affect programmer-observable behaviour. It is essential, both for programming and verification, to abstract from such microarchitectural details as much as possible, but no more. We explore the key architecture design questions with a series of examples, discussed in detail with senior Arm staff; capture the architectural intent in operational and axiomatic semantic models, extending previous work on “user-mode” concurrency; make these models executable as test oracles for small examples; and experimentally validate them against hardware behaviour (finding a bug in one hardware device). We thereby bring these subtle issues into the mathematical domain, clarifying the architecture and enabling future work on system software verification.This work was partially supported by EPSRC grant EP/K008528/1 (REMS), ERC Advanced Grant 789108 (ELVER), an ARM iCASE award, and ARM donation funding. % This work is part of the CIFV project sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL), under contract FA8650-18-C-7809. The views, opinions, and/or findings contained in this paper are those of the authors and should not be interpreted as representing the official views or policies, either expressed or implied, of the Department of Defense or the U.S. Government