291 research outputs found

    Stream Fusion, to Completeness

    Full text link
    Stream processing is mainstream (again): Widely-used stream libraries are now available for virtually all modern OO and functional languages, from Java to C# to Scala to OCaml to Haskell. Yet expressivity and performance are still lacking. For instance, the popular, well-optimized Java 8 streams do not support the zip operator and are still an order of magnitude slower than hand-written loops. We present the first approach that represents the full generality of stream processing and eliminates overheads, via the use of staging. It is based on an unusually rich semantic model of stream interaction. We support any combination of zipping, nesting (or flat-mapping), sub-ranging, filtering, mapping-of finite or infinite streams. Our model captures idiosyncrasies that a programmer uses in optimizing stream pipelines, such as rate differences and the choice of a "for" vs. "while" loops. Our approach delivers hand-written-like code, but automatically. It explicitly avoids the reliance on black-box optimizers and sufficiently-smart compilers, offering highest, guaranteed and portable performance. Our approach relies on high-level concepts that are then readily mapped into an implementation. Accordingly, we have two distinct implementations: an OCaml stream library, staged via MetaOCaml, and a Scala library for the JVM, staged via LMS. In both cases, we derive libraries richer and simultaneously many tens of times faster than past work. We greatly exceed in performance the standard stream libraries available in Java, Scala and OCaml, including the well-optimized Java 8 streams

    Mobile Resource Guarantees for Smart Devices

    Get PDF
    Abstract. We present the Mobile Resource Guarantees framework: a system for ensuring that downloaded programs are free from run-time violations of resource bounds. Certificates are attached to code in the form of efficiently checkable proofs of resource bounds; in contrast to cryptographic certificates of code origin, these are independent of trust networks. A novel programming language with resource constraints encoded in function types is used to streamline the generation of proofs of resource usage.

    Symbolic and analytic techniques for resource analysis of Java bytecode

    Get PDF
    Recent work in resource analysis has translated the idea of amortised resource analysis to imperative languages using a program logic that allows mixing of assertions about heap shapes, in the tradition of separation logic, and assertions about consumable resources. Separately, polyhedral methods have been used to calculate bounds on numbers of iterations in loop-based programs. We are attempting to combine these ideas to deal with Java programs involving both data structures and loops, focusing on the bytecode level rather than on source code

    Automatic transformation of iterative loops into recursive methods

    Full text link
    NOTICE: this is the author’s version of a work that was accepted for publication in Information and Software Technology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information and Software Technology, [Volume 58, February 2015, Pages 95–109] DOI 10.1016/j.infsof.2014.10.001[EN] Context In software engineering, taking a good election between recursion and iteration is essential because their efficiency and maintenance are different. In fact, developers often need to transform iteration into recursion (e.g., in debugging, to decompose the call graph into iterations); thus, it is quite surprising that there does not exist a public transformation from loops to recursion that can be used in industrial projects (i.e., it is automatic, it handles all kinds of loops, it considers exceptions, etc.). Objective This article describes an industrial algorithm implemented as a Java library able to automatically transform iterative loops into equivalent recursive methods. The transformation is described for the programming language Java, but it is general enough as to be adapted to many other languages that allow iteration and recursion. Method We describe the changes needed to transform loops of types while/do/for/foreach into recursion. We provide a transformation schema for each kind of loop. Results Our algorithm is the first public transformation that can be used in industrial projects and faces the whole Java language (i.e., it is fully automatic, it handles all kinds of loops, it considers exceptions, it treats the control statements break and continue, it handles loop labels, it is able to transform any number of nested loops, etc.). This is particularly interesting because some of these features are missing in all previous work, probably, due to the complexity that their mixture introduce in the transformation. Conclusion Developers should use a methodology when transforming code, specifically when transforming loops into recursion. This article provides guidelines and algorithms that allow them to face different problems such as exception handling. The implementation has been made publicly available as open source.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economia y Competitividad (Secretaria de Estado de Investigacion, Desarrollo e Innovacion) under Grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under Grant PROMETEO/2011/052. David Insa was partially supported by the Spanish Ministerio de Educacion under FPU Grant AP2010-4415.Insa Cabrera, D.; Silva, J. (2015). Automatic transformation of iterative loops into recursive methods. Information and Software Technology. 58:95-109. https://doi.org/10.1016/j.infsof.2014.10.001S951095

    Aspects of functional programming

    Get PDF
    This thesis explores the application of functional programming in new areas and its implementation using new technologies. We show how functional languages can be used to implement solutions to problems in fuzzy logic using a number of languages: Haskell, Ginger and Aladin. A compiler for the weakly-typed, lazy language Ginger is developed using Java byte-code as its target code. This is used as the inspiration for an implementation of Aladin, a simple functional language which has two novel features: its primitives are designed to be written in any language, and evaluation is controlled by declaring the strictness of all functions. Efficient denotational and operational semantics are given for this machine and an implementation is devel- oped using these semantics. We then show that by using the advantages of Aladin (simplicity and strictness control) we can employ partial evaluation to achieve con- siderable speed-ups in the running times of Aladin programs

    Language run-time systems:An overview

    Get PDF
    The proliferation of high-level programming languages with advanced language features and the need for portability across increasingly heterogeneous and hierarchical architectures require a sophisticated run-time system to manage program execution and available resources. Additional benefits include isolated execution of untrusted code and the potential for dynamic optimisation, among others. This paper provides a high-level overview of language run-time systems with a focus on execution models, support for concurrency and parallelism, memory management, and communication, whilst briefly mentioning synchronisation, monitoring, and adaptive policy control. Two alternative approaches to run-time system design are presented and several challenges for future research are outlined. References to both seminal and recent work are provided

    Micro Virtual Machines: A Solid Foundation for Managed Language Implementation

    Get PDF
    Today new programming languages proliferate, but many of them suffer from poor performance and inscrutable semantics. We assert that the root of many of the performance and semantic problems of today's languages is that language implementation is extremely difficult. This thesis addresses the fundamental challenges of efficiently developing high-level managed languages. Modern high-level languages provide abstractions over execution, memory management and concurrency. It requires enormous intellectual capability and engineering effort to properly manage these concerns. Lacking such resources, developers usually choose naive implementation approaches in the early stages of language design, a strategy which too often has long-term consequences, hindering the future development of the language. Existing language development platforms have failed to provide the right level of abstraction, and forced implementers to reinvent low-level mechanisms in order to obtain performance. My thesis is that the introduction of micro virtual machines will allow the development of higher-quality, high-performance managed languages. The first contribution of this thesis is the design of Mu, with the specification of Mu as the main outcome. Mu is the first micro virtual machine, a robust, performant, and light-weight abstraction over just three concerns: execution, concurrency and garbage collection. Such a foundation attacks three of the most fundamental and challenging issues that face existing language designs and implementations, leaving the language implementers free to focus on the higher levels of their language design. The second contribution is an in-depth analysis of on-stack replacement and its efficient implementation. This low-level mechanism underpins run-time feedback-directed optimisation, which is key to the efficient implementation of dynamic languages. The third contribution is demonstrating the viability of Mu through RPython, a real-world non-trivial language implementation. We also did some preliminary research of GHC as a Mu client. We have created the Mu specification and its reference implementation, both of which are open-source. We show that that Mu's on-stack replacement API can gracefully support dynamic languages such as JavaScript, and it is implementable on concrete hardware. Our RPython client has been able to translate and execute non-trivial RPython programs, and can run the RPySOM interpreter and the core of the PyPy interpreter. With micro virtual machines providing a low-level substrate, language developers now have the option to build their next language on a micro virtual machine. We believe that the quality of programming languages will be improved as a result
    • …
    corecore