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共 567 条记录，以下是111-120 订阅

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IRDL: An IR Definition language for SSA Compilers 2022

IRDL: An IR Definition Language for SSA Compilers

引用

43rd acm sigplan International conference on programming language design and implementation (pldi)

作者： Fehr, Mathieu Niu, Jeff Riddle, River Amini, Mehdi Su, Zhendong Grosser, Tobias Univ Edinburgh Edinburgh Midlothian Scotland Univ Waterloo Waterloo ON Canada Modular AI Seattle WA USA Google Mountain View CA USA Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9781450392655

designing compiler intermediate representations (IRs) is often a manual process that makes exploration and innovation in this space costly. Developers typically use general-purpose programming languages to design IRs. As a result, IR implementations are verbose, manual modifications are expensive, and designing tooling for the inspection or generation of IRs is impractical. While compilers relied historically on a few slowly evolving IRs, domain-specific optimizations and specialized hardware motivate compilers to use and evolve many IRs. We facilitate the implementation of SSA-based IRs by introducing IRDL, a domain-specific language to define IRs. We analyze all 28 domain-specific IRs developed as part of LLVM's MLIR project over the last two years and demonstrate how to express these IRs exclusively in IRDL while only rarely falling back to IRDL's support for generic C++ extensions. By enabling the concise and explicit specification of IRs, we provide foundations for developing effective tooling to automate the compiler construction process.

关键词： Compilers Intermediate Representation MLIR

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A single intermediate language that supports multiple implementations of exceptions

A single intermediate language that supports multiple implem...

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acm sigplan' 00 conference on programming language design and implementation (pldi)

作者： Ramsey, N Jones, SP Harvard Univ Cambridge MA 02138 USA

We present mechanisms that enable our compiler-target language, C--, to express four of the best known techniques for implementing exceptions, all within a single, uniform framework. We define the mechanisms precisely, using a formal operational semantics. We also show that exceptions need not require special treatment in the optimizer;by introducing extra dataflow edges, we make standard optimization techniques work even on programs that use exceptions. Our approach clarifies the design space of exception-handling techniques, and it allows a single optimizer to handle a variety of implementation techniques. Our ultimate goal is to allow a source-language compiler the freedom to choose its exception-handling policy, while encapsulating the architecture-dependent mechanisms and their optimization in an implementation of C-- that can be used by compilers for many source languages.

关键词： C (programming language)

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Compiling Stan to Generative Probabilistic languages and Extension to Deep Probabilistic programming 2021

Compiling Stan to Generative Probabilistic Languages and Ext...

引用

42nd acm sigplan International conference on programming language design and implementation (pldi)

作者： Baudart, Guillaume Burroni, Javier Hirzel, Martin Mandel, Louis Shinnar, Avraham PSL Univ Ecole Normale Super INRIA Paris Paris France UMass Amherst Amherst MA USA IBM Res MIT IBM Watson AI Lab Armonk NY USA

ISBN: (纸本)9781450383912

Stan is a probabilistic programming language that is popular in the statistics community, with a high-level syntax for expressing probabilistic models. Stan differs by nature from generative probabilistic programming languages like Church, Anglican, or Pyro. This paper presents a comprehensive compilation scheme to compile any Stan model to a generative language and proves its correctness. We use our compilation scheme to build two new backends for the Stanc3 compiler targeting Pyro and NumPyro. Experimental results show that the NumPyro backend yields a 2.3x speedup compared to Stan in geometric mean over 26 benchmarks. Building on Pyro we extend Stan with support for explicit variational inference guides and deep probabilistic models. That way, users familiar with Stan get access to new features without having to learn a fundamentally new language.

关键词： Probabilistic programming Semantics Stan Pyro

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Probabilistic programming with Programmable Inference 2018

Probabilistic Programming with Programmable Inference

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39th acm sigplan conference on programming language design and implementation (pldi)

作者： Mansinghka, Vikash K. Schaechtle, Ulrich Handa, Shivam Radul, Alexey Chen, Yutian Rinard, Martin MIT Cambridge MA 02139 USA Google DeepMind London England

ISBN: (纸本)9781450356985

We introduce inference metaprogramming for probabilistic programming languages, including new language constructs, a formalism, and the first demonstration of effectiveness in practice. Instead of relying on rigid black-box inference algorithms hard-coded into the language implementation as in previous probabilistic programming languages, inference metaprogramming enables developers to 1) dynamically decompose inference problems into subproblems, 2) apply inference tactics to subproblems, 3) alternate between incorporating new data and performing inference over existing data, and 4) explore multiple execution traces of the probabilistic program at once. Implemented tactics include gradient-based optimization, Markov chain Monte Carlo, variational inference, and sequental Monte Carlo techniques. Inference metaprogramming enables the concise expression of probabilistic models and inference algorithms across diverse fields, such as computer vision, data science, and robotics, within a single probabilistic programming language.

关键词： Probabilistic programming Semantics Inference

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Typed Self-Representation 09

Typed Self-Representation

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acm sigplan conference on programming language design and implementation

作者： Rendel, Tillmann Ostermann, Klaus Hofer, Christian Univ Aarhus DK-8000 Aarhus C Denmark

ISBN: (纸本)9781605583921

Self-representation - the ability to represent programs in their own language - has important applications in reflective languages and many other domains of programming language design. Although approaches to designing typed program representations for sublanguages of some base language have become quite popular recently, the question whether a fully metacircular typed self-representation is possible is still open. This paper makes a big step towards this aim by defining the F(omega)* calculus, an extension of the higher-order polymorphic lambda calculus F. that allows type self-representations. While the usability of these representations for metaprogramming is still limited, we believe that our approach makes a significant step towards a new generation of reflective languages that are both safe and efficient.

关键词： Lambda Calculus language design Reflection Self Interpretation Types

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A General Constraint-centric Scheduling Framework for Spatial Architectures

A General Constraint-centric Scheduling Framework for Spatia...

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34th acm sigplan conference on programming language design and implementation (pldi)

作者： Nowatzki, Tony Sartin-Tarm, Michael De Carli, Lorenzo Sankaralingam, Karthikeyan Estan, Cristian Robatmili, Behnam Univ Wisconsin Madison WI 53706 USA

ISBN: (纸本)9781450320146

Specialized execution using spatial architectures provides energy efficient computation, but requires effective algorithms for spatially scheduling the computation. Generally, this has been solved with architecture-specific heuristics, an approach which suffers from poor compiler/architect productivity, lack of insight on optimality, and inhibits migration of techniques between architectures. Our goal is to develop a scheduling framework usable for all spatial architectures. To this end, we expresses spatial scheduling as a constraint satisfaction problem using Integer Linear programming (ILP). We observe that architecture primitives and scheduler responsibilities can be related through five abstractions: placement of computation, routing of data, managing event timing, managing resource utilization, and forming the optimization objectives. We encode these responsibilities as 20 general ILP constraints, which are used to create schedulers for the disparate TRIPS, DySER, and PLUG architectures. Our results show that a general declarative approach using ILP is implementable, practical, and typically matches or outperforms specialized schedulers.

关键词： Spatial Architectures Spatial Architecture Scheduling Integer Linear programming

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FAST: a Transducer-Based language for Tree Manipulation 14

FAST: a Transducer-Based Language for Tree Manipulation

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35th acm sigplan conference on programming language design and implementation (pldi)

作者： D'Antoni, Loris Veanes, Margus Livshits, Benjamin Molnar, David Univ Penn Philadelphia PA 19104 USA

ISBN: (纸本)9781450327848

Tree automata and tree transducers are used in a wide range of applications in software engineering, from XML processing to language type-checking. While these formalisms are of immense practical use, they can only model finite alphabets, and since many real-world applications operate over in finite domains such as integers, this is often a limitation. To overcome this problem we augment tree automata and transducers with symbolic alphabets represented as parametric theories. Admitting in finite alphabets makes these models more general and succinct than their classical counterparts. Despite this, we show how the main operations, such as composition and language equivalence, remain computable given a decision procedure for the alphabet theory. We introduce a high-level language called Fast that acts as a front-end for the above formalisms. Fast supports symbolic alphabets through tight integration with state-of-the art satisfiability modulo theory (SMT) solvers. We demonstrate our techniques on practical case studies, covering a wide range of applications.

关键词： Symbolic Tree Transducers FAST

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Achieving High Coverage for Floating-Point Code via Unconstrained programming 2017

Achieving High Coverage for Floating-Point Code via Unconstr...

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38th acm sigplan conference on programming language design and implementation (pldi)

作者： Fu, Zhoulai Su, Zhendong Univ Calif Davis Davis CA 95616 USA

ISBN: (纸本)9781450349888

Achieving high code coverage is essential in testing, which gives us confidence in code quality. Testing floating-point code usually requires painstaking efforts in handling floating-point constraints, e.g., in symbolic execution. This paper turns the challenge of testing floating-point code into the opportunity of applying unconstrained programming-the mathematical solution for calculating function minimum points over the entire search space. Our core insight is to derive a representing function from the floating-point program, any of whose minimum points is a test input guaranteed to exercise a new branch of the tested program. This guarantee allows us to achieve high coverage of the floating-point program by repeatedly minimizing the representing function. We have realized this approach in a tool called CoverMe and conducted an extensive evaluation of it on Sun's C math library. Our evaluation results show that CoverMe achieves, on average, 90.8% branch coverage in 6.9 seconds, drastically outperforming our compared tools: (1) Random testing, (2) AFL, a highly optimized, robust fuzzer released by Google, and (3) Austin, a state-of-the-art coverage-based testing tool designed to support floating-point code.

关键词： Unconstrained programming Representing Function CoverMe

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Dynamic Enforcement of Determinism in a Parallel Scripting language 14

Dynamic Enforcement of Determinism in a Parallel Scripting L...

引用

35th acm sigplan conference on programming language design and implementation (pldi)

作者： Lu, Li Ji, Weixing Scott, Michael L. Univ Rochester Rochester NY 14627 USA Beijing Inst Technol Beijing Peoples R China

ISBN: (纸本)9781450327848

Determinism is an appealing property for parallel programs, as it simplifies understanding, reasoning and debugging. It is particularly appealing in dynamic (scripting) languages, where ease of programming is a dominant design goal. Some existing parallel languages use the type system to enforce determinism statically, but this is not generally practical for dynamic languages. In this paper, we describe how determinism can be obtained-and dynamically enforced/verified-for appropriate extensions to a parallel scripting language. Specifically, we introduce the constructs of Deterministic Parallel Ruby (DPR), together with a run-time system (TARDIS) that verifies properties required for determinism, including correct usage of reductions and commutative operators, and the mutual independence (data-race freedom) of concurrent tasks. Experimental results confirm that DPR can provide scalable performance on multicore machines and that the overhead of TARDIS is low enough for practical testing. In particular, TARDIS significantly outperforms alternative data-race detectors with comparable functionality. We conclude with a discussion of future directions in the dynamic enforcement of determinism.

关键词： design languages Reliability Determinism deterministic parallelism data races scripting language

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Guaranteed Bounds for Posterior Inference in Universal Probabilistic programming 2022

Guaranteed Bounds for Posterior Inference in Universal Proba...

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43rd acm sigplan International conference on programming language design and implementation (pldi)

作者： Beutner, Raven Ong, C-H Luke Zaiser, Fabian CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Univ Oxford Oxford England

ISBN: (纸本)9781450392655

We propose a new method to approximate the posterior distribution of probabilistic programs by means of computing guaranteed bounds. The starting point of our work is an interval-based trace semantics for a recursive, higher-order probabilistic programming language with continuous distributions. Taking the form of (super-/subadditive) measures, these lower/upper bounds are non-stochastic and provably correct: using the semantics, we prove that the actual posterior of a given program is sandwiched between the lower and upper bounds (soundness);moreover, the bounds converge to the posterior (completeness). As a practical and sound approximation, we introduce a weight-aware interval type system, which automatically infers interval bounds on not just the return value but also the weight of program executions, simultaneously. We have built a tool implementation, called GuBPI, which automatically computes these posterior lower/upper bounds. Our evaluation on examples from the literature shows that the bounds are useful, and can even be used to recognise wrong outputs from stochastic posterior inference procedures.

关键词： probabilistic programming Bayesian inference verification abstract interpretation operational semantics interval arithmetic type system symbolic execution

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