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Increasing data set sizes motivate for a shift of focus from computation-centric systems to data-centric systems, where data movement is treated as a first-class optimization metric. An example of this emerging paradigm is in-situ computing in largescale computing systems. Observing that data movement costs are increasing at an exponential rate even at a node level (as a node itself is fast-becoming...
Aggregators are market participants that bridge the gap between the bulk electricity market and the emerging active end-user (smart home) by efficiently scheduling or allocating resources to meet certain objectives in the electricity grid. The computational burden and processing time of such allocation problems increases with the number of resources. Using high performance computing and parallel processing...
The solution of the problem of construction of generalized model of production system optimal development is considered. Basis of the model — Bolza variational problem with integrated criterion of the first kind. Solution of the problem by numerical method is based on the method of optimal aggregation of “production, development” structures by simulation method of Hamilton function determination and...
This paper presents a numerical comparison between the second order cone relaxation for single-phase distribution systems and the semidefinite relaxation for the multiphase distribution systems for the optimal power flow problem considering unbalanced load and generation. Towards this end, the IEEE 37-bus test feeder is adapted using four different distribution line models for the various feeder segments...
The paper presents a two-stage model for achieving feasible optimal solution along with numerical validation for the exactness of the available second order cone relaxation in the distribution optimal power flow problem. To this end, the IEEE 13-bus, 34-bus and 123-bus distribution power systems are adapted by balancing the various feeder segments and by populating selected nodes with photovoltaic...
Various methods of identifying cellular automaton models and their state transition functions, in particular, have been proposed. Among these, a method that uses ℓ1-norm optimization can be applied to multi-valued cellular automaton models. When solving this optimization problem, it is important to reduce the computational cost as the size of the problem increases. In this paper, we present a method...
In the paper the approaches how to develop models of electrotechnical objects using the test example of two-winding transformer are discussed. A comparing of the continuous model created using the description of physical processes and discrete macromodel obtained using the “black box” approach based on field experiment are carried out. It is shown that the model obtained using the “black box” approach...
Modeling helps explain the fundamental physics hidden behind experimental data. In the case of material modeling, running one simulation rarely results in output that reproduces the experimental data. Often one or more of the force field parameters are not precisely known and must be optimized for the output to match that of the experiment. Since the simulations require high performance computing...
The point spread function (PSF), namely the response of an ultrasound system to a point source, is a powerful measure of the quality of an imaging system. The lack of an analytical formulation inhibits many applications ranging from apodization optimization, array-design, and deconvolution algorithms. We propose to fill this gap through a general PSF derivation that is flexible with respect to the...
Compute-intensive GPU architectures allow the use of high-order 3D stencils for better computational accuracy. These stencils are usually compute-bound. While current state-of-the-art register allocators are satisfactory for most applications, they are unable to effectively manage register pressure for such complex high-order stencils, resulting in a sub-optimal code with a large number of register...
This paper presents two models of AC optimal power flow based Financial Transmission Rights (FTRs) allocation auction. Both models were compared with the conventional DC optimal power flow (DC-OPF) based model. Considering an FTR between two nodes as a real power injection at the source node and a power withdrawal at the sink node; the first model assumes that the net power due to FTRs equals zero...
In this paper, we present a system that supports the design of web graphical user interface by finding the optimal placement of interactive elements. The definition of optimal placement is context specific; it aims at maximizing measurable aspects of the user experience, and it is derived using expert knowledge embedded in the system, which is based on HCI principles, user studies, and data analytics...
Simulation Optimization is computationally expensive, especially in large-scale stochastic problem solving, where the computational budget is considered as an important factor. A higher computational budget attempts to generate highly accurate solutions while a lower budget might result in biased or unrealistic solutions. In this paper, the effect of computational budget on the quality of the solution,...
Demand is mounting in the industry for scalable GPU-based deep learning systems. Unfortunately, existing training applications built atop popular deep learning frameworks, including Caffe, Theano, and Torch, etc, are incapable of conducting distributed GPU training over large-scale clusters.To remedy such a situation, this paper presents Nexus, a platform that allows existing deep learning frameworks...
This paper presents a tool-supported flow for exploring the design space of an FPGA-based application, which is the Scale-Invariant Feature Transform (SIFT), a common image feature detection algorithm used as key component in computer vision tasks such as advanced driver assistance systems (ADAS). The proposed system is based on a dedicated hardware accelerator tightly coupled to a soft-core VLIW...
Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose...
Scattered data fitting is always a challenging problem in the fields of geometric modeling and computer aided design. As the skeleton based three-dimensional solid model representation, the Ball B-Spline Curve is suitable to fit the tubular scattered data points. We study the problem of fitting the scattered data points with Ball B-spline curves (BBSCs) and propose the corresponding fitting algorithm...
We propose CDONE, a convex version of the DONE algorithm. DONE is a derivative-free online optimization algorithm that uses surrogate modeling with noisy measurements to find a minimum of objective functions that are expensive to evaluate. Inspired by their success in deep learning, CDONE makes use of rectified linear units, together with a nonnegativity constraint to enforce convexity of the surrogate...
This paper introduces a new approach for solving the navigation problem of Unmanned Aerial Vehicles (UAV) by studying its rotational and translational dynamics and then solving the nonlinear model by the Decomposition Coordination method. The objective is to reach a destination goal by the mean of an autonomous computed optimal path calculated through optimal control sequence. Solving such complex...
Current hybrid network-on-chip designs in manycore systems are agnostic to the application requirements and thus are provided for general cases. This results in high cost in the manycore systems design, wasted energy and performance. We observe that the cost of network-on-chip designs can be reduced by optimizing the application-specific traffic onto the system. This paper presents mincostflow-based...
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