2,557 research outputs found
An overview of the ciao multiparadigm language and program development environment and its design philosophy
We describe some of the novel aspects and motivations behind
the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system
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Preparing sparse solvers for exascale computing.
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'
Towards Formal Interaction-Based Models of Grid Computing Infrastructures
Grid computing (GC) systems are large-scale virtual machines, built upon a
massive pool of resources (processing time, storage, software) that often span
multiple distributed domains. Concurrent users interact with the grid by adding
new tasks; the grid is expected to assign resources to tasks in a fair,
trustworthy way. These distinctive features of GC systems make their
specification and verification a challenging issue. Although prior works have
proposed formal approaches to the specification of GC systems, a precise
account of the interaction model which underlies resource sharing has not been
yet proposed. In this paper, we describe ongoing work aimed at filling in this
gap. Our approach relies on (higher-order) process calculi: these core
languages for concurrency offer a compositional framework in which GC systems
can be precisely described and potentially reasoned about.Comment: In Proceedings DCM 2013, arXiv:1403.768
High-Performance Cloud Computing: A View of Scientific Applications
Scientific computing often requires the availability of a massive number of
computers for performing large scale experiments. Traditionally, these needs
have been addressed by using high-performance computing solutions and installed
facilities such as clusters and super computers, which are difficult to setup,
maintain, and operate. Cloud computing provides scientists with a completely
new model of utilizing the computing infrastructure. Compute resources, storage
resources, as well as applications, can be dynamically provisioned (and
integrated within the existing infrastructure) on a pay per use basis. These
resources can be released when they are no more needed. Such services are often
offered within the context of a Service Level Agreement (SLA), which ensure the
desired Quality of Service (QoS). Aneka, an enterprise Cloud computing
solution, harnesses the power of compute resources by relying on private and
public Clouds and delivers to users the desired QoS. Its flexible and service
based infrastructure supports multiple programming paradigms that make Aneka
address a variety of different scenarios: from finance applications to
computational science. As examples of scientific computing in the Cloud, we
present a preliminary case study on using Aneka for the classification of gene
expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape
Next generation software environments : principles, problems, and research directions
The past decade has seen a burgeoning of research and development in software environments. Conferences have been devoted to the topic of practical environments, journal papers produced, and commercial systems sold. Given all the activity, one might expect a great deal of consensus on issues, approaches, and techniques. This is not the case, however. Indeed, the term "environment" is still used in a variety of conflicting ways. Nevertheless substantial progress has been made and we are at least nearing consensus on many critical issues.The purpose of this paper is to characterize environments, describe several important principles that have emerged in the last decade or so, note current open problems, and describe some approaches to these problems, with particular emphasis on the activities of one large-scale research program, the Arcadia project. Consideration is also given to two related topics: empirical evaluation and technology transition. That is, how can environments and their constituents be evaluated, and how can new developments be moved effectively into the production sector
An Object-Oriented Model for Extensible Concurrent Systems: the Composition-Filters Approach
Applying the object-oriented paradigm for the development of large and complex software systems offers several advantages, of which increased extensibility and reusability are the most prominent ones. The object-oriented model is also quite suitable for modeling concurrent systems. However, it appears that extensibility and reusability of concurrent applications is far from trivial. The problems that arise, the so-called inheritance anomalies are analyzed and presented in this paper. A set of requirements for extensible concurrent languages is formulated. As a solution to the identified problems, an extension to the object-oriented model is presented; composition filters. Composition filters capture messages and can express certain constraints and operations on these messages, for example buffering. In this paper we explain the composition filters approach, demonstrate its expressive power through a number of examples and show that composition filters do not suffer from the inheritance anomalies and fulfill the requirements that were established
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