6,301 research outputs found

    S-Net for multi-memory multicores

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    Copyright ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 5th ACM SIGPLAN Workshop on Declarative Aspects of Multicore Programming: http://doi.acm.org/10.1145/1708046.1708054S-Net is a declarative coordination language and component technology aimed at modern multi-core/many-core architectures and systems-on-chip. It builds on the concept of stream processing to structure dynamically evolving networks of communicating asynchronous components. Components themselves are implemented using a conventional language suitable for the application domain. This two-level software architecture maintains a familiar sequential development environment for large parts of an application and offers a high-level declarative approach to component coordination. In this paper we present a conservative language extension for the placement of components and component networks in a multi-memory environment, i.e. architectures that associate individual compute cores or groups thereof with private memories. We describe a novel distributed runtime system layer that complements our existing multithreaded runtime system for shared memory multicores. Particular emphasis is put on efficient management of data communication. Last not least, we present preliminary experimental data

    Preliminary Design of the APIARY for VLSI Support of Knowledge-Based Systems

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    This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Office of Naval Research of the Department of Defense under Contract N00014-75-C-0522.Knowledge-based applications will require vastly increased computational resources to achieve their goals. We are working on the development of a VLSI Message Passing Architecture to meet this need. As a first step we present the preliminary design of the APIARY system in this paper. The APIARY is currently in an early stage of implementation at the MIT Artificial Intelligence Laboratory.MIT Artificial Intelligence Laboratory Department of Defense Office of Naval Researc

    Real-time and fault tolerance in distributed control software

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    Closed loop control systems typically contain multitude of spatially distributed sensors and actuators operated simultaneously. So those systems are parallel and distributed in their essence. But mapping this parallelism onto the given distributed hardware architecture, brings in some additional requirements: safe multithreading, optimal process allocation, real-time scheduling of bus and network resources. Nowadays, fault tolerance methods and fast even online reconfiguration are becoming increasingly important. All those often conflicting requirements, make design and implementation of real-time distributed control systems an extremely difficult task, that requires substantial knowledge in several areas of control and computer science. Although many design methods have been proposed so far, none of them had succeeded to cover all important aspects of the problem at hand. [1] Continuous increase of production in embedded market, makes a simple and natural design methodology for real-time systems needed more then ever

    PKind: A parallel k-induction based model checker

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    PKind is a novel parallel k-induction-based model checker of invariant properties for finite- or infinite-state Lustre programs. Its architecture, which is strictly message-based, is designed to minimize synchronization delays and easily accommodate the incorporation of incremental invariant generators to enhance basic k-induction. We describe PKind's functionality and main features, and present experimental evidence that PKind significantly speeds up the verification of safety properties and, due to incremental invariant generation, also considerably increases the number of provable ones.Comment: In Proceedings PDMC 2011, arXiv:1111.006

    Load sharing for optimistic parallel simulations on multicore machines

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    Parallel Discrete Event Simulation (PDES) is based on the partitioning of the simulation model into distinct Logical Processes (LPs), each one modeling a portion of the entire system, which are allowed to execute simulation events concurrently. This allows exploiting parallel computing architectures to speedup model execution, and to make very large models tractable. In this article we cope with the optimistic approach to PDES, where LPs are allowed to concurrently process their events in a speculative fashion, and rollback/ recovery techniques are used to guarantee state consistency in case of causality violations along the speculative execution path. Particularly, we present an innovative load sharing approach targeted at optimizing resource usage for fruitful simulation work when running an optimistic PDES environment on top of multi-processor/multi-core machines. Beyond providing the load sharing model, we also define a load sharing oriented architectural scheme, based on a symmetric multi-threaded organization of the simulation platform. Finally, we present a real implementation of the load sharing architecture within the open source ROme OpTimistic Simulator (ROOT-Sim) package. Experimental data for an assessment of both viability and effectiveness of our proposal are presented as well. Copyright is held by author/owner(s)

    Predictive analysis and optimisation of pipelined wavefront applications using reusable analytic models

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    Pipelined wavefront computations are an ubiquitous class of high performance parallel algorithms used for the solution of many scientific and engineering applications. In order to aid the design and optimisation of these applications, and to ensure that during procurement platforms are chosen best suited to these codes, there has been considerable research in analysing and evaluating their operational performance. Wavefront codes exhibit complex computation, communication, synchronisation patterns, and as a result there exist a large variety of such codes and possible optimisations. The problem is compounded by each new generation of high performance computing system, which has often introduced a previously unexplored architectural trait, requiring previous performance models to be rewritten and reevaluated. In this thesis, we address the performance modelling and optimisation of this class of application, as a whole. This differs from previous studies in which bespoke models are applied to specific applications. The analytic performance models are generalised and reusable, and we demonstrate their application to the predictive analysis and optimisation of pipelined wavefront computations running on modern high performance computing systems. The performance model is based on the LogGP parameterisation, and uses a small number of input parameters to specify the particular behaviour of most wavefront codes. The new parameters and model equations capture the key structural and behavioural differences among different wavefront application codes, providing a succinct summary of the operations for each application and insights into alternative wavefront application design. The models are applied to three industry-strength wavefront codes and are validated on several systems including a Cray XT3/XT4 and an InfiniBand commodity cluster. Model predictions show high quantitative accuracy (less than 20% error) for all high performance configurations and excellent qualitative accuracy. The thesis presents applications, projections and insights for optimisations using the model, which show the utility of reusable analytic models for performance engineering of high performance computing codes. In particular, we demonstrate the use of the model for: (1) evaluating application configuration and resulting performance; (2) evaluating hardware platform issues including platform sizing, configuration; (3) exploring hardware platform design alternatives and system procurement and, (4) considering possible code and algorithmic optimisations
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