Métaprogrammation | EPFL Graph Search

La métaprogrammation, , désigne l'écriture de programmes qui manipulent des données décrivant elles-mêmes des programmes. Dans le cas particulier où le programme manipule ses propres instructions pendant son exécution, on parle de programme auto-modifiant. Elle peut être employée pour générer du code interprété par un compilateur et donner un résultat constant, afin d'éviter un calcul manuel. Il permet également de réduire le temps d'exécution du programme si le résultat constant avait été classiquement calculé par le programme comme pour les résultats variables. Cette méthode ne s'applique pas uniquement aux calculs mais aussi au remplissage de données constantes telles que des tableaux ou des structures plus complexes. Cependant cette technique ne fonctionne que pour des valeurs constantes. En effet, si une donnée manipulée par le métaprogramme est une entrée du programme, par exemple une saisie de l’utilisateur, elle ne peut pas être connue avant l'exécution du programme. Il est d

Surgical Precision JIT Compilers

Hassan Chafi, Tiark Rompf

Just-in-time (JIT) compilation of running programs provides more optimization opportunities than offline compilation. Modern JIT compilers, such as those in virtual machines like Oracle's HotSpot for Java or Google's V8 for JavaScript, rely on dynamic profiling as their key mechanism to guide optimizations. While these JIT compilers offer good average performance, their behavior is a black box and the achieved performance is highly unpredictable. In this paper, we propose to turn JIT compilation into a precision tool by adding two essential and generic metaprogramming facilities: First, allow programs to invoke JIT compilation explicitly. This enables controlled specialization of arbitrary code at run-time, in the style of partial evaluation. It also enables the JIT compiler to report warnings and errors to the program when it is unable to compile a code path in the demanded way. Second, allow the JIT compiler to call back into the program to perform compile-time computation. This lets the program itself define the translation strategy for certain constructs on the fly and gives rise to a powerful JIT macro facility that enables "smart" libraries to supply domain-specific compiler optimizations or safety checks. We present Lancet, a JIT compiler framework for Java bytecode that enables such a tight, two-way integration with the running program. Lancet itself was derived from a high-level Java bytecode interpreter: staging the interpreter using LMS (Lightweight Modular Staging) produced a simple bytecode compiler. Adding abstract interpretation turned the simple compiler into an optimizing compiler. This fact provides compelling evidence for the scalability of the staged-interpreter approach to compiler construction. In the case of Lancet, JIT macros also provide a natural interface to existing LMS-based toolchains such as the Delite parallelism and DSL framework, which can now serve as accelerator macros for arbitrary JVM bytecode.

Assoc Computing Machinery2014

Type-Safe Metaprogramming and Compilation Techniques For Designing Efficient Systems in High-Level Languages

Lionel Emile Vincent Parreaux

Software engineering practices have been steadily moving towards higher-level programming languages and away from lower-level ones. High-level languages tend to greatly improve safety, productivity, and code maintainability because they handle various implementation details automatically, allowing programmers to focus on their problem domains. However, the gains offered by high-level languages are usually made at the cost of reduced performance: higher-level languages usually consume more memory, run more slowly and require expensive garbage-collecting runtime systems. This trend has been worsening with the increasing adoption of the functional programming paradigm by the industry. Modern programmers are thus faced with a dilemma: should they favor productivity and lower maintenance costs at the expense of performance, or should they focus on performance, to the detriments of almost everything else? The main idea behind this thesis is that we can help solve this dilemma by making advances in type systems, metaprogramming, and compilers technology. In particular, we study how metaprogramming via statically-typed quasiquotation can let programmers define their own domain-specific optimizations in a safe way, while leveraging the latest advances in intermediate program representations. We present the design and implementation of the Squid metaprogramming framework, which extends the Scala programming language with multi-staged programming capabilities and more. We also present different application examples for Squid, including a polymorphic yet efficient library for linear algebra, a stream fusion engine improving on the state of the art, a demonstration of query compilation by rewriting, a staged SQL database system prototype, and a new embedded domain-specific language for expressing queries over collections of data.

EPFL2020

Proof of Multi-Stage Programming with Generative and Analytical Macros

Jonathan Immanuel Brachthäuser, Martin Odersky, Nicolas Alexander Stucki

In metaprogramming, code generation and code analysis are complementary. Traditionally, principled metaprogramming extensions for programming languages, like MetaML and BER MetaOCaml, offer strong foundations for code generation but lack equivalent support for code analysis. Similarly, existing macro systems are biased towards the code generation aspect. In this work, we present a calculus for macros featuring both code generation and code analysis. The calculus directly models separate compilation of macros, internalizing a commonly neglected aspect of macros. The system ensures that the generated code is well-typed and hygienic. We implement our system in Scala 3, provide a formalization, and prove its soundness.

EPFL2021

Surgical Precision JIT Compilers

Hassan Chafi, Tiark Rompf

Assoc Computing Machinery2014