Increasingly, multi-core processors, multi-processor nodes and multi-core, multi-processor nodes are finding their way into computer clusters. Clusters built using such nodes are already quite common and, inevitably, ...
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Increasingly, multi-core processors, multi-processor nodes and multi-core, multi-processor nodes are finding their way into computer clusters. Clusters built using such nodes are already quite common and, inevitably, will become more so over time. As with any new technology, however, the potential benefits are seldom as easy to attain as we expect them to be. In this paper, we explore three fundamental issues related to the use of multi-core, multi-processor nodes in compute clusters using MPI: inter-communication (messaging) efficiency, cache effects (in particular processor affinity) and initial process distribution. Based on some initial experiments using a subset of the NAS parallel benchmarks running on a small scale cluster with dual core, dual processor nodes, we report results on the impact of these issues. From these results we attempt to extrapolate some simple, guidelines that are likely to be generally applicable for optimizing MPI code running on clusters with multi- core, multi-processor nodes.
Background: Clinical protocols and guidelines have been considered as a major means to ensure that cost-effective services are provided at the point of care. Recently, the computerisation of clinical guidelines has at...
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Background: Clinical protocols and guidelines have been considered as a major means to ensure that cost-effective services are provided at the point of care. Recently, the computerisation of clinical guidelines has attracted extensive research interest. Many languages and frameworks have been developed. Thus far, however, an enactment mechanism to facilitate decentralised guideline execution has been a largely neglected line of research. It is our contention that decentralisation is essential to maintain a high-performance system in pervasive health care scenarios. In this paper, we propose the use of Lightweight Coordination Calculus (LCC) as a feasible solution. LCC is a light-weight and executable process calculus that has been used successfully in multi-agent systems, peer-to-peer (p2p) computer networks, etc. In light of an envisaged pervasive health care scenario, LCC, which represents clinical protocols and guidelines as message-based interaction models, allows information exchange among software agents distributed across different departments and/or hospitals. Results: We outlined the syntax and semantics of LCC;proposed a list of refined criteria against which the appropriateness of candidate clinical guideline modelling languages are evaluated;and presented two LCC interaction models of real life clinical guidelines. Conclusions: We demonstrated that LCC is particularly useful in modelling clinical guidelines. It specifies the exact partition of a workflow of events or tasks that should be observed by multiple "players" as well as the interactions among these "players". LCC presents the strength of both process calculi and Horn clauses pair of which can provide a close resemblance of logic programming and the flexibility of practical implementation.
Since the process technology of LSI devices are developing, the process variation becomes a more critical issue. Especially, the clock skew, which is produced by fabrication variation, causes the serious defects for f...
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Since the process technology of LSI devices are developing, the process variation becomes a more critical issue. Especially, the clock skew, which is produced by fabrication variation, causes the serious defects for fabricated chip functions. To improve this problem, the several deskew methods using Programmable Delay Elements (PDEs) have been proposed. However, they need much test cost and PDE cost for an industrial application. We propose a novel method with less PDEs and less test cost by Linear programming (LP). The proposed method calculates the each PDE delay using the feasibility check of LP. Our experiment shows that the nondefective chip rate after applying deskew increase 91.6% with 4 PDEs while the nondefective chip rate before applying deskew are 21.2%. The experimental result confirms that our proposed method is effective for improving the yields and relaxing the design margin.
In the last decade, the size and complexity of the software in embedded systems have increased. The present study attempts to decrease the complexity and difficulty of software development in embedded systems. We here...
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In the last decade, the size and complexity of the software in embedded systems have increased. The present study attempts to decrease the complexity and difficulty of software development in embedded systems. We herein introduce a new component system that is suitable for embedded systems. It is possible to estimate the memory consumption of an entire application since the proposed system adopts a static configuration. In addition, this system takes into account to be used in several domains of embedded systems because several particle sizes of component are supported. Moreover, the concept of the component for a distributed application is presented
AUTOSAR (AUTOmotive Open System ARchitecture) consortium is a development partnership between the main actors of the automotive manufacturing industry. It aims at defining an open standardized software architecture, i...
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AUTOSAR (AUTOmotive Open System ARchitecture) consortium is a development partnership between the main actors of the automotive manufacturing industry. It aims at defining an open standardized software architecture, in order to face the future challenges in automotive development. One of the important challenge concerns the development of time-critical systems, e.g. brake-by-wire or steer-by-wire. In order to master the development of such systems, one must be able to understand and analyze their real-time behavior. Responses to this problem can be found in the real-time scheduling theory, especially schedulability analysis techniques. In this paper, we propose a review of a subset of the AUTOSAR Operating System specification from a schedulability analysis point-of-view.
This paper presents GAPSYS - a genetic algorithm based automated circuit synthesis tool for passive analog circuits. It describes the procedure for developing both the circuit topology and the component values for a p...
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This paper presents GAPSYS - a genetic algorithm based automated circuit synthesis tool for passive analog circuits. It describes the procedure for developing both the circuit topology and the component values for a passive analog circuit comprising of R, L and C components from a given set of specifications. The novelty of the work pertains to the component value assignment procedure for the initial set of circuits and the crossover techniques employed. Experiments conducted on two low-pass filter design benchmarks demonstrate the effectiveness of GAPSYS as a synthesis tool.
In this paper, a peak-constrained weighted least-squares (PCWLS) method is presented for designing a general FIR digital filter with constant group delay passband, using the projected least-squares (PLS) algorithm. In...
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In this paper, a peak-constrained weighted least-squares (PCWLS) method is presented for designing a general FIR digital filter with constant group delay passband, using the projected least-squares (PLS) algorithm. In the design of a general FIR filter, peak error constraints are nonlinear functions of filter coefficients and can not be accepted by the PLS algorithm. In the proposed method, peak error constraints are formulated, through some approximation, as a set of linear inequalities to be incorporated into the design problem. Design examples show the effectiveness of the peak error control of the proposed method.
In this paper, an approximate optimal control-based neurocontroller for guiding the seedlings growth in greenhouse is presented. The main goal of this approach is to obtain a close-loop operation with a state neurocon...
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In this paper, an approximate optimal control-based neurocontroller for guiding the seedlings growth in greenhouse is presented. The main goal of this approach is to obtain a close-loop operation with a state neurocontroller, whose design is based on approximate optimal control theory. The neurocontroller drives the progress of the crop growth development while minimizing a predefined cost function in terms of operative costs and final state errors under physical constraints on process variables and actuator signals. The aim is to find an approximate optimal control policy to guide the development of tomato seedlings from an initial to a desired state by controlling the greenhouse's microclimate. In this paper we propose an indirect measuring of the seedlings growth state using artificial vision. In order to show the performance and practical feasibility of the proposed approach, an experiment was carried out for the development of tomato seedings
We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian decision problems when the training data is composed of the trajectory of some fixed behaviour policy. ...
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We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian decision problems when the training data is composed of the trajectory of some fixed behaviour policy. The algorithm studied is policy iteration where in successive iterations the action-value functions of the intermediate policies are obtained by means of approximate value iteration. PAC-style polynomial bounds are derived on the number of samples needed to guarantee near-optimal performance. The bounds depend on the mixing rate of the trajectory, the smoothness properties of the underlying Markovian decision problem, the approximation power and capacity of the function set used. One of the main novelties of the paper is that new smoothness constraints are introduced thereby significantly extending the scope of previous results.
In this paper, we give an overview of Seymour's matroid decomposition theory in the context of binary linear codes, and discuss some of its implications for linear programming (LP) decoding of a binary linear code...
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ISBN:
(纸本)9781424413973
In this paper, we give an overview of Seymour's matroid decomposition theory in the context of binary linear codes, and discuss some of its implications for linear programming (LP) decoding of a binary linear code. As shown by Feldman et al. maximum-likelihood (ML) decoding over a discrete memoryless channel can be formulated as an LP problem. Using this formulation, we translate matroid-theoretic results of Grotschel and Truemper from the combinatorial optimization literature as examples of non-trivial families of codes for which ML decoding can be implemented in time polynomial in the length of the code. However, we also show that such families of codes are not good in a coding-theoretic sense - either their dimension or their minimum distance must grow sub-linearly with codelength.
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