Contification using dominators

FluetMatthew,; WeeksStephen,

doi:10.1145/507669.507639

Cited by 13 publications

(18 citation statements)

References 23 publications

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“…To evaluate and compare the dominance test implementations, we measure both the building time of the dominance test, and its practical cost in time, when using it. 8 Results are presented in Figure 3 and Figure 4. The building time of the dominance test is the time, in seconds, required to compute the function test_dom: node → node → bool.…”

Section: Resultsmentioning

confidence: 99%

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Validating Dominator Trees for a Fast, Verified Dominance Test

Blazy

Demange

Pichardie

2015

Interactive Theorem Proving

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The problem of computing dominators in a control flow graph is central to numerous modern compiler optimizations. Many efficient algorithms have been proposed in the litterature, but mechanizing the correctness of the most sophisticated algorithms is still considered as too hard problems, and to this date, verified compilers use less optimized implementations. In contrast, production compilers, like GCC or LLVM, implement the classic, efficient Lengauer-Tarjan algorithm [12], to compute dominator trees. And subsequent optimization phases can then determine whether a CFG node dominates another node in constant time by using their respective depth-first search numbers in the dominator tree. In this work, we aim at integrating such techniques in verified compilers. We present a formally verified validator of untrusted dominator trees, on top of which we implement and prove correct a fast dominance test following these principles. We conduct our formal development in the Coq proof assistant, and integrate it in the middle-end of the CompCertSSA verified compiler. We also provide experimental results showing performance improvement over previous formalizations.

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Section: Resultsmentioning

confidence: 99%

“…Other CPS or ANF-based verified compilers for functional languages [3,6] implement simple optimizations that do not require dominance information, although their (unverified) peers, like MLton, benefit from dominators for, e.g. contification [8] for inter-procedural optimization.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Validating Dominator Trees for a Fast, Verified Dominance Test

Blazy

Demange

Pichardie

2015

Interactive Theorem Proving

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“…Contification [7] is an optimization that turns a function into a continuation when the function is only ever called with the same continuation argument. This makes control flow more explicit, thus potentially enabling subsequent optimizations.…”

Section: Contificationmentioning

confidence: 99%

Pilsner: a compositionally verified compiler for a higher-order imperative language

Neis

Hur

Kaiser

et al. 2015

Proceedings of the 20th ACM SIGPLAN International Conference on Functional Programming

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Compiler verification is essential for the construction of fully verified software, but most prior work (such as CompCert) has focused on verifying whole-program compilers. To support separate compilation and to enable linking of results from different verified compilers, it is important to develop a compositional notion of compiler correctness that is modular (preserved under linking), transitive (supports multi-pass compilation), and flexible (applicable to compilers that use different intermediate languages or employ non-standard program transformations).In this paper, building on prior work of Hur et al., we develop a novel approach to compositional compiler verification based on parametric inter-language simulations (PILS). PILS are modular: they enable compiler verification in a manner that supports separate compilation. PILS are transitive: we use them to verify Pilsner, a simple (but non-trivial) multi-pass optimizing compiler (programmed in Coq) from an ML-like source language S to an assembly-like target language T, going through a CPS-based intermediate language. Pilsner is the first multi-pass compiler for a higher-order imperative language to be compositionally verified. Lastly, PILS are flexible: we use them to additionally verify (1) Zwickel, a direct non-optimizing compiler for S, and (2) a handcoded self-modifying T module, proven correct w.r.t. an S-level specification. The output of Zwickel and the self-modifying T module can then be safely linked together with the output of Pilsner. All together, this has been a significant undertaking, involving several person-years of work and over 55,000 lines of Coq.

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“…Monadic normal forms offer the main advantages of CPS (i.e., all intermediate results are named and their computation is sequentialized), 1 and they have been used in compilers for functional languages [7,6,21,22,23,38,40,46]. Therefore, a one-pass transformation into monadic normal form with short-cut boolean evaluation could well be of practical use (i.e., outside academia).…”

Section: O Danvymentioning

confidence: 99%