161 resultados para Controller framework


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The memory subsystem is a major contributor to the performance, power, and area of complex SoCs used in feature rich multimedia products. Hence, memory architecture of the embedded DSP is complex and usually custom designed with multiple banks of single-ported or dual ported on-chip scratch pad memory and multiple banks of off-chip memory. Building software for such large complex memories with many of the software components as individually optimized software IPs is a big challenge. In order to obtain good performance and a reduction in memory stalls, the data buffers of the application need to be placed carefully in different types of memory. In this paper we present a unified framework (MODLEX) that combines different data layout optimizations to address the complex DSP memory architectures. Our method models the data layout problem as multi-objective genetic algorithm (GA) with performance and power being the objectives and presents a set of solution points which is attractive from a platform design viewpoint. While most of the work in the literature assumes that performance and power are non-conflicting objectives, our work demonstrates that there is significant trade-off (up to 70%) that is possible between power and performance.

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Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop.

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In an approach directed toward a tashironin based complex natural product, efficacy of the singlet oxygen mediated [4+2]-cycloaddition to a tetracyclic cyclopentadiene has been evaluated to install the key cis-1,4-dihydroxy functionality. (C) 2011 Elsevier Ltd. All rights reserved.

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This paper proposes a framework of designing for conceptual and early embodiment design that uses physical laws and effects explicitly as a central aspect for designing. This is especially important in domains that make explicit use of physical laws and effects in their design, such as novel sensors. The objectives of the paper are: (a) Develop a model, (b) Empirically evaluate the model and (c) Propose a framework. The model is developed by integrating the activity- and outcome-based elements. The model is validated empirically by analyzing protocols of design sessions to find instances of activities and outcomes. Based on the findings, a framework is proposed on how designing should be done. Elements of GEMS (Generate-Evaluate-Modify-Select) and SAPPhIRE (State change-Action-Part-Phenomenon-Input-oRgan-Effect) are used for developing the model.Empirical evaluation confirms that designing can be modeled with the activity and outcome elements. The paper concludes with the identification of areas that require support and future work.

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Rate control regulates the instantaneous video bit -rate to maximize a picture quality metric while satisfying channel constraints. Typically, a quality metric such as Peak Signalto-Noise ratio (PSNR) or weighted signal -to-noise ratio(WSNR) is chosen out of convenience. However this metric is not always truly representative of perceptual video quality.Attempts to use perceptual metrics in rate control have been limited by the accuracy of the video quality metrics chosen.Recently, new and improved metrics of subjective quality such as the Video quality experts group's (VQEG) NTIA1 General Video Quality Model (VQM) have been proven to have strong correlation with subjective quality. Here, we apply the key principles of the NTIA -VQM model to rate control in order to maximize perceptual video quality. Our experiments demonstrate that applying NTIA -VQM motivated metrics to standard TMN8 rate control in an H.263 encoder results in perceivable quality improvements over a baseline TMN8 / MSE based implementation.

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This paper presents a robust fixed order H2controller design using strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H2controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation

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Highly luminescent micrometre-sized fine particles of a Zn(II) metal-organic framework (MOF) of a new pi-electron rich tricarboxylate dispersed in ethanol is demonstrated as a selective sensory material for the detection of nitroaromatic explosives via a fluorescence quenching mechanism.

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A reaction of copper acetate, 5-nitroisophthalic acid in a water-methanol mixture under solvothermal condition results in a new metal-organic framework compound, [Cu(5)(mu(3)-OH)(2)(H(2)O)(6){(NO(2))-C(6)H(3)-(COO)(2)}(4)]center dot 5H(2)O, (1). The compound contains Cu5 pentameric cluster units connected by 5-nitro isophthalate (NIPA) moieties forming a CdCl(2)-like layer, which are further connected by another NIPA moiety forming the three-dimensional structure. The water molecules in (1) can be reversibly adsorbed. The removal of water accompanies a change in the colour as well as a structural re-organization. Magnetic studies suggest strong antiferromagnetie correlations between the Cu5 cluster units. The compound (1) exhibits heterogeneous Lewis acid catalysis for the cyanosilylation of imines with more than 95 % selectivity. Compound (1) has been characterized by IR, UV-vis, TGA, powder XRD studies.

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The success of an ABV IP depends highly on the associated debugging environment. An efficient debugging environment helps the user to find out the exact location of the failure. Moreover, it provides information to the user in a refined detail of abstraction and permit adequate interaction. It has also been realized that adequate visualization support helps in tracking the behavioral aspects of the Design Under Test (DUT). Currently, the debugging tools provide information in the signal level and do not provide any information about the high-level behavior of the DUT. We present a debugging framework that takes the design specification, assertions and the user intent in a simple format and provides detailed information by processing the design trace on-line, or off-line. We also present a visualization framework to ease the debugging procedure. We have experimented with industrial standard on-chip bus protocols that ensure that this utility can be incorporated successfully in the present functional verification flow.

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In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.