Declarative Foreign Function Binding Through Generic Programming

Yallop, Jeremy; Sheets, David; Madhavapeddy, Anil

doi:10.1007/978-3-319-29604-3_13

Cited by 2 publications

(1 citation statement)

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“…In the context of OCaml [Leroy et al 2014], we are not aware of any work aiming to optimise across FFI calls, but attempts have been made to cross this boundary at a different level. The construction of type-safe wrappers over the FFI on the OCaml side is an active area of research [Yallop et al 2016] and type systems were also developed in order to verify the correctness of C callees [Furr and Foster 2005]. Such prior work is encouraging as it shows that a common ground exists and the memory models and object representations of the two languages can be bridged by analyses.…”

Section: Background and Related Workmentioning

confidence: 99%

Duplo: a framework for OCaml post-link optimisation

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Jones

2020

Proc. ACM Program. Lang.

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We present a novel framework, Duplo, for the low-level post-link optimisation of OCaml programs, achieving a speedup of 7% and a reduction of at least 15% of the code size of widely-used OCaml applications. Unlike existing post-link optimisers, which typically operate on target-specific machine code, our framework operates on a Low-Level Intermediate Representation (LLIR) capable of representing both the OCaml programs and any C dependencies they invoke through the foreign-function interface (FFI). LLIR is analysed, transformed and lowered to machine code by our post-link optimiser, LLIR-OPT. Most importantly, LLIR allows the optimiser to cross the OCaml-C language boundary, mitigating the overhead incurred by the FFI and enabling analyses and transformations in a previously unavailable context. The optimised IR is then lowered to amd64 machine code through the existing target-specific code generator of LLVM, modified to handle garbage collection just as effectively as the native OCaml backend. We equip our optimiser with a suite of SSA-based transformations and points-to analyses capable of capturing the semantics and representing the memory models of both languages, along with a cross-language inliner to embed C methods into OCaml callers. We evaluate the gains of our framework, which can be attributed to both our optimiser and the more sophisticated amd64 backend of LLVM, on a wide-range of widely-used OCaml applications, as well as an existing suite of microand macro-benchmarks used to track the performance of the OCaml compiler.

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Section: Background and Related Workmentioning

confidence: 99%