Modern real-time embedded applications present high computation requirements which need to be realized within strict time constraints. the current trend towards parallelprocessing in the embedded domain allows provid...
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Modern real-time embedded applications present high computation requirements which need to be realized within strict time constraints. the current trend towards parallelprocessing in the embedded domain allows providing higher processing power. However, in some embedded applications, the use of powerful enough multi-core processors, may not be possible due to energy, space or cost constraints. A solution for this problem is to extend the parallel execution of the applications, allowing them to distribute their workload among networked nodes, on peak situations, to remote neighbour nodes in the system. In this context, we present the Partitioned-distributed-Deadline Monotonic Scheduling algorithm for fork-join parallel/distributed fixed-priority tasks. We study the problem of scheduling fork-join tasks that execute in a distributed system, where the inherent transmission delay of tasks must be considered and cannot be deemed negligible, as in the case of multicore systems. Our scheduling algorithm is shown to have a resource augmentation bound of 4, which implies that any task set that is feasible on m unit-speed processors and a single shared real-time network, can be scheduled by our algorithm on m processors and a single real-time network that are 4 times faster. We confirm through simulations our analytical results.
In this study, a control method is proposed to improve the harmonic suppression efficiency of the single phase active power filter in a distorted power system environment. Here, we present a method to use self-tuning ...
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In this study, a control method is proposed to improve the harmonic suppression efficiency of the single phase active power filter in a distorted power system environment. Here, we present a method to use self-tuning filter (STF) algorithm for single phase active power filter. the proposed method process the grid voltage in order to provide a uniform reference grid current to increase efficiency of the system. the results of simulation study are presented to verify the effectiveness of the proposed control technique in this study.
the Current Controlled Voltage Source Inverter (CCVSI) has attracted substantial research due to its common application for the integration of renewable energy resources into the main grid. the single loop current con...
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the Current Controlled Voltage Source Inverter (CCVSI) has attracted substantial research due to its common application for the integration of renewable energy resources into the main grid. the single loop current controller is commonly used in industry for CCVSI due to its simplicity, desirable stability margins and dynamic performance. For the single loop controller, the point of common coupling (PCC) voltage feedforward control is used to improve the transient and disturbance rejection performance. However, this solution exhibits one drawback that has not yet been adequately discussed in the literature: the poor stability caused by the feedforward control itself. It is proved that the feedforward voltage results in a “positive feedback control” which essentially degrades the stability of the system and its control performance. Since the gain of the “positive feedback control” depends on the grid impedance, it is necessary to study how the stability and control performance of the grid parallel inverter is affected by the feedforward control under various grid impedances. the system without feedforward control is also investigated due the fact that the grid impedance generally affects the system stability. the analytical study shows that two cases have similar performance under stiff grid, while the case without feedforward has superior stability and control performance under weak grid impedance. the simulation and experimental results also validate the outcome of the analytical study.
Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive softwar...
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Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive software,which takes adaptability as an inherent feature and can act as the foundation of the engineering *** introducing AUModel,the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled,which can facilitate boththe development and maintenance of adaptive *** paper also presents our initial attempts to realize this model,including a middleware prototype to support this model and an application to validate its effectiveness.
the relevance of graphical functions in vehicular applications has increased significantly during the last years. Modern cars are equipped with multiple displays used by different applications such as speedometer, nav...
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the relevance of graphical functions in vehicular applications has increased significantly during the last years. Modern cars are equipped with multiple displays used by different applications such as speedometer, navigation system, or media players. the recent trend towards hardware consolidation to reduce hardware cost, installation space, and energy consumption, causes graphical 3D applications of different safety-criticality to share a single GPU. this requires effective real-time GPU scheduling concepts to ensure safety and isolation for 3D rendering. Since current GPUs are not preemptible, a deadline-based scheduler must know the GPU execution time of GPU commands in advance. In this work, we present a novel framework to measure and predict the execution time of GPU commands using OpenGL ES 2.0. We present prediction models for the main GPU commands relevant for 3D rendering, namely, FLUSH, CLEAR, and DRAW. For the DRAW command we propose to use the 3D bounding box of the rendered model and apply the vertex shader projection to heuristically estimate the number of fragments rendered. We finally present the implementation and evaluation of our framework, which demonstrates its feasibility and shows that good prediction accuracy can be achieved. In our evaluation using realistic scenarios the absolute prediction error of the DRAW command did not exceed 260 μs.
the proceedings contain 323 papers. the topics discussed include: experiences withthe sparse matrix-vector multiplication on a many-core processor;performance benefits of heterogeneous computing in HPC workloads;ther...
ISBN:
(纸本)9780769546766
the proceedings contain 323 papers. the topics discussed include: experiences withthe sparse matrix-vector multiplication on a many-core processor;performance benefits of heterogeneous computing in HPC workloads;thermal-aware performance optimization in power constrained heterogenous data centers;experiences with target-platform heterogeneity in clouds, grids, and on-premises resources;blor: bandwidth and latency sensitive overlay routing for flash data dissemination;scheduling batch and heterogeneous jobs with runtime elasticity in a parallelprocessing environment;task scheduling in large-scale distributed systems utilizing partial reconfigurable processing elements;mixed data-parallel scheduling for distributed continuous integration;a monte-carlo approach for full-ahead stochastic DAG scheduling;a block-asynchronous relaxation method for graphics processing units;and partitioning for parallel matrix-matrix multiplication with heterogeneous processors: the optimal solution.
the proceedings contain 118 papers. the topics discussed include: a predictive model for solving small linear algebra problems in GPU registers;a parallel tiled solver for dense symmetric indefinite systems on multico...
ISBN:
(纸本)9780769546759
the proceedings contain 118 papers. the topics discussed include: a predictive model for solving small linear algebra problems in GPU registers;a parallel tiled solver for dense symmetric indefinite systems on multicore architectures;a comprehensive study of task coalescing for selecting parallelism granularity in a two-stage bidiagonal reduction;improving the performance of dynamical simulations via multiple right-hand sides;high-performance interaction-based simulation of gut immunopathologies with enteric immunity simulator (ENISI);a parallel algorithm for spectrum-based short read error correction;enhancing the scalability of consistency-based progressive multiple sequences alignment applications;an accurate GPU performance model for effective control flow divergence optimization;power-aware Manhattan routing on chip multiprocessors;and efficient resource oblivious algorithms for multicores with false sharing.
We present a parallel algorithm for finding all Pareto optimal paths from a specified source in a graph. the algorithm is label-setting, i.e., it only performs work on distance labels that are optimal. the main result...
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ISBN:
(纸本)9780769549712
We present a parallel algorithm for finding all Pareto optimal paths from a specified source in a graph. the algorithm is label-setting, i.e., it only performs work on distance labels that are optimal. the main result is that the added complexity when going from one to multiple objectives is completely parallelizable. the algorithm is based on a multi-objective generalization of a priority queue. Such a Pareto queue can be efficiently implemented for two dimensions. Surprisingly, the parallel biobjective approach yields an algorithm performing asymptotically less work than the previous sequential algorithms. We also discuss generalizations for d >= 3 objective functions and for single target search.
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