47,708 research outputs found

    A Direct-Style Effect Notation for Sequential and Parallel Programs

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    Modeling sequential and parallel composition of effectful computations has been investigated in a variety of languages for a long time. In particular, the popular do-notation provides a lightweight effect embedding for any instance of a monad. Idiom bracket notation, on the other hand, provides an embedding for applicatives. First, while monads force effects to be executed sequentially, ignoring potential for parallelism, applicatives do not support sequential effects. Composing sequential with parallel effects remains an open problem. This is even more of an issue as real programs consist of a combination of both sequential and parallel segments. Second, common notations do not support invoking effects in direct-style, instead forcing a rigid structure upon the code. In this paper, we propose a mixed applicative/monadic notation that retains parallelism where possible, but allows sequentiality where necessary. We leverage a direct-style notation where sequentiality or parallelism is derived from the structure of the code. We provide a mechanisation of our effectful language in Coq and prove that our compilation approach retains the parallelism of the source program

    A Direct-Style Effect Notation for Sequential and Parallel Programs (Artifact)

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    Modeling sequential and parallel composition of effectful computations has been investigated in a variety of languages for a long time. In particular, the popular do-notation provides a lightweight effect embedding for any instance of a monad. Idiom bracket notation, on the other hand, provides an embedding for applicatives. First, while monads force effects to be executed sequentially, ignoring potential for parallelism, applicatives do not support sequential effects. Composing sequential with parallel effects remains an open problem. This is even more of an issue as real programs consist of a combination of both sequential and parallel segments. Second, common notations do not support invoking effects in direct-style, instead forcing a rigid structure upon the code. In this paper, we propose a mixed applicative/monadic notation that retains parallelism where possible, but allows sequentiality where necessary. We leverage a direct-style notation where sequentiality or parallelism is derived from the structure of the code. We provide a mechanisation of our effectful language in Coq and prove that our compilation approach retains the parallelism of the source program

    Systematic composition of distributed objects: Processes and sessions

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    We consider a system with the infrastructure for the creation and interconnection of large numbers of distributed persistent objects. This system is exemplified by the Internet: potentially, every appliance and document on the Internet has both persistent state and the ability to interact with large numbers of other appliances and documents on the Internet. This paper elucidates the characteristics of such a system, and proposes the compositional requirements of its corresponding infrastructure. We explore the problems of specifying, composing, reasoning about and implementing applications in such a system. A specific concern of our research is developing the infrastructure to support structuring distributed applications by using sequential, choice and parallel composition, in the anarchic environment where application compositions may be unforeseeable and interactions may be unknown prior to actually occurring. The structuring concepts discussed are relevant to a wide range of distributed applications; our implementation is illustrated with collaborative Java processes interacting over the Internet, but the methodology provided can be applied independent of specific platforms

    An interactive semantics of logic programming

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    We apply to logic programming some recently emerging ideas from the field of reduction-based communicating systems, with the aim of giving evidence of the hidden interactions and the coordination mechanisms that rule the operational machinery of such a programming paradigm. The semantic framework we have chosen for presenting our results is tile logic, which has the advantage of allowing a uniform treatment of goals and observations and of applying abstract categorical tools for proving the results. As main contributions, we mention the finitary presentation of abstract unification, and a concurrent and coordinated abstract semantics consistent with the most common semantics of logic programming. Moreover, the compositionality of the tile semantics is guaranteed by standard results, as it reduces to check that the tile systems associated to logic programs enjoy the tile decomposition property. An extension of the approach for handling constraint systems is also discussed.Comment: 42 pages, 24 figure, 3 tables, to appear in the CUP journal of Theory and Practice of Logic Programmin

    A distributed Real-Time Java system based on CSP

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    CSP is a fundamental concept for developing software for distributed real time systems. The CSP paradigm constitutes a natural addition to object orientation and offers higher order multithreading constructs. The CSP channel concept that has been implemented in Java deals with single- and multi-processor environments and also takes care of the real time priority scheduling requirements. For this, the notion of priority and scheduling has been carefully examined and as a result it was reasoned that priority scheduling should be attached to the communicating channels rather than to the processes. In association with channels, a priority based parallel construct is developed for composing processes: hiding threads and priority indexing from the user. This approach simplifies the use of priorities for the object oriented paradigm. Moreover, in the proposed system, the notion of scheduling is no longer connected to the operating system but has become part of the application instead

    Distributed measurement-based quantum computation

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    We develop a formal model for distributed measurement-based quantum computations, adopting an agent-based view, such that computations are described locally where possible. Because the network quantum state is in general entangled, we need to model it as a global structure, reminiscent of global memory in classical agent systems. Local quantum computations are described as measurement patterns. Since measurement-based quantum computation is inherently distributed, this allows us to extend naturally several concepts of the measurement calculus, a formal model for such computations. Our goal is to define an assembly language, i.e. we assume that computations are well-defined and we do not concern ourselves with verification techniques. The operational semantics for systems of agents is given by a probabilistic transition system, and we define operational equivalence in a way that it corresponds to the notion of bisimilarity. With this in place, we prove that teleportation is bisimilar to a direct quantum channel, and this also within the context of larger networks.Comment: 17 page

    GraphX: Unifying Data-Parallel and Graph-Parallel Analytics

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    From social networks to language modeling, the growing scale and importance of graph data has driven the development of numerous new graph-parallel systems (e.g., Pregel, GraphLab). By restricting the computation that can be expressed and introducing new techniques to partition and distribute the graph, these systems can efficiently execute iterative graph algorithms orders of magnitude faster than more general data-parallel systems. However, the same restrictions that enable the performance gains also make it difficult to express many of the important stages in a typical graph-analytics pipeline: constructing the graph, modifying its structure, or expressing computation that spans multiple graphs. As a consequence, existing graph analytics pipelines compose graph-parallel and data-parallel systems using external storage systems, leading to extensive data movement and complicated programming model. To address these challenges we introduce GraphX, a distributed graph computation framework that unifies graph-parallel and data-parallel computation. GraphX provides a small, core set of graph-parallel operators expressive enough to implement the Pregel and PowerGraph abstractions, yet simple enough to be cast in relational algebra. GraphX uses a collection of query optimization techniques such as automatic join rewrites to efficiently implement these graph-parallel operators. We evaluate GraphX on real-world graphs and workloads and demonstrate that GraphX achieves comparable performance as specialized graph computation systems, while outperforming them in end-to-end graph pipelines. Moreover, GraphX achieves a balance between expressiveness, performance, and ease of use
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