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At least 55 records · Page 3

Linear optimization - A case study in performance analysis

The paper deals with the performance of two parallel variants of the simplex algorithm on a message-passing system. First, the simplex algorithm is reviewed, two possible parallelizations of the algorithm are discussed, and results of benchmark speedups of the alternatives are presented. Between column and row partitionings, the row partitioning method is found to be generally superior, while the column partitioning method is more efficient when the number of rows is small, and the number of columns is much greater that the number of rows. Various performance analysis tools are then applied to examine the reasons for relative performance differences, and communication idle time due to global minimization and load imbalances is noted as the main factor in execution slowdown.

Stunkel, Craig B.↗

Iterative methods in GPU-resident linear solvers for nonlinear constrained optimization

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where traditional sparse numerical linear algebra methods are often inefficient. For example, methods for solving ill-conditioned linear systems have relied on conditional branching, which degrades performance on hardware accelerators such as graphical processing units (GPUs). To improve the efficiency of solving ill-conditioned systems, our computational strategy separates computations that are efficient on GPUs from those that need to run on traditional central processing units (CPUs). Our strategy maximizes the reuse of expensive CPU computations. Iterative methods, which thus far have not been broadly used for ill-conditioned linear systems, play an important role in our approach. In particular, we extend ideas from Arioli et al., (2007) to implement iterative refinement using inexact LU factors and flexible generalized minimal residual (FGMRES), with the aim of efficient performance on GPUs. In conclusion, we focus on solutions that are effective within broader application contexts, and discuss how early performance tests could be improved to be more predictive of the performance in a realistic environment.

97 MATHEMATICS AND COMPUTING↗

On the relationship between reliability and linear quadratic optimal control

The linear quadratic optimal control method is used today to solve many complex systems problems. As system complexity increases, and as linear quadratic optimal control is used in more demanding situations, the extension of the design methodology to cover system failures, robustness and reliability is of crucial importance. This paper documents the progress toward a theory which incorporates reliability in the performance index; a linear quadratic control problem is formulated which accounts for system effectiveness and gives an offline procedure for comparing two linear quadratic control systems on the basis of both reliability and performance.

Birdwell, J. D.↗

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequency control methods that are able to stabilize a disturbance in the power system at timescales comparable to the fast converter dynamics. This paper proposes a combined linear and neural network controller for inverter-based primary frequency control that is stable at time-varying levels of inertia. We model the time-variance in inertia via a switched affine hybrid system model. We derive stability certificates for the proposed controller via a quadratic candidate Lyapunov function. We test the proposed control on a 12-bus 3-area test network, and compare its performance with a base case linear controller, optimized linear controller, and finite-horizon Linear Quadratic Regulator (LQR). Our proposed controller achieves faster mean settling time and over 50% reduction in average control cost across 100 inertia scenarios compared to the optimized linear controller. Unlike LQR which requires complete knowledge of the inertia trajectories and system dynamics over the entire control time horizon, our proposed controller is real-time tractable, and achieves comparable performance to LQR.

data-driven control↗

The synthesis of optimal controls for linear, time-optimal problems with retarded controls.

Optimization problems involving linear systems with retardations in the controls are studied in a systematic way. Some physical motivation for the problems is discussed. The topics covered are: controllability, existence and uniqueness of the optimal control, sufficient conditions, techniques of synthesis, and dynamic programming. A number of solved examples are presented.

Banks, H. T.↗

Development of a Distribution Optimal Power Flow Federate for Open-Source OEDI-SI Platform

Increasing numbers of distributed generators in the electric power distribution networks require developing a control strategy to optimize solutions in real time. Linearized optimal distribution flow development has seen growth and acceptance in the distribution systems literature for efficiently modeling the \glspl{opf} for distribution systems. This paper examines the implementation and integration procedure for linearized optimal distribution flow federate to \gls{oedisi} platform. Specifically, we discuss i) the usage of the \gls{oedisi} platform, ii) obtaining a tractable solution using developed \gls{opf} federate, and iii) validation of solutions and bench-marking the \gls{oedisi} platform with developed \gls{opf} federate using OpenDSS. In brief, we demonstrate how a general linearized optimal distribution flow federate can be developed and integrated with a co-simulation environment to mimic real-world examples. The efficacy of the proposed method is demonstrated using the IEEE 123-bus test system under different scenarios to obtain a tractable solution and compare its results.

Sadnan, Rabayet↗

Optimizing a Linear Array of Radiating Elements

EOPS empirically optimizes linear array of radiating elements. Program directly addresses problem of minimizing maximum side-lobe level of fixed length, linear arrays of radiating elements under realistic "on-the-vehicle" conditions. Used for both electromagnetic and acoustic arrays.

Blank, S. J.↗

A widefield fluorescence microscope with a linear image sensor for image cytometry of biospecimens: Considerations for image quality optimization

Linear image sensors have been widely used in numerous research and industry applications to provide continuous imaging of moving objects. Here, we present a widefield fluorescence microscope with a linear image sensor used to image translating objects for image cytometry. First, a calibration curve was characterized for a custom microfluidic chamber over a span of volumetric pump rates. Image data were also acquired using 15 μm fluorescent polystyrene spheres on a slide with a motorized translation stage in order to match linear translation speed with line exposure periods to preserve the image aspect ratio. Aspect ratios were then calculated after imaging to ensure quality control of image data. Fluorescent beads were imaged in suspension flowing through the microfluidics chamber being pumped by a mechanical syringe pump at 16 μl min{sup −1} with a line exposure period of 150 μs. The line period was selected to acquire images of fluorescent beads with a 40 dB signal-to-background ratio. A motorized translation stage was then used to transport conventional glass slides of stained cellular biospecimens. Whole blood collected from healthy volunteers was stained with 0.02% (w/v) proflavine hemisulfate was imaged to highlight leukocyte morphology with a 1.56 mm × 1.28 mm field of view (1540 ms total acquisition time). Oral squamous cells were also collected from healthy volunteers and stained with 0.01% (w/v) proflavine hemisulfate to demonstrate quantifiable subcellular features and an average nuclear to cytoplasmic ratio of 0.03 (n = 75), with a resolution of 0.31 μm pixels{sup −1}.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Preliminary software development for optical mirror figure control

The maintenance of accurate primary mirror figure in the face of environmental disturbances is the key to the achievement of diffraction-limited performance in a large space telescope. In order to develop the concepts of optical mirror figure control, an experimental program was initiated. A major component in this experiment will be an XDS Sigma 5.7 digital computer which will realize the control algorithm. A software package is described which realizes linear optimal, simplified linear, and iterative optimal control algorithms. The software, in addition, provides for interactive communication between the operator and the computer, and interaction between the computer and the experimental hardware elements. A brief description of a small hybrid computer system is also presented.

Mackinnon, D.↗

An algorithm for optimal single linear feature extraction from several Gaussian pattern classes

A computational algorithm is presented for the extraction of an optimal single linear feature from several Gaussian pattern classes. The algorithm minimizes the increase in the probability of misclassification in the transformed (feature) space. Numerical results on the application of this procedure to the remotely sensed data from the Purdue Cl flight line as well as LANDSAT data are presented. It was found that classification using the optimal single linear feature yielded a value for the probability of misclassification on the order of 30% less than that obtained by using the best single untransformed feature. Also, the optimal single linear feature gave performance results comparable to those obtained by using the two features which maximized the average divergence.

Starks, S. A.↗