Implementation Variants Research Articles

Stability of multiobjective predictive control: A utopia-tracking approach

We propose a utopia-tracking strategy to handle multiple conflicting objectives in model predictive control. The controller minimizes the distance of its vector of objectives to that of the compromise solution: the point along the steady-state Pareto front closest to the utopia point, where all the objectives are independently minimized. We establish conditions for asymptotic stability and propose numerical implementation variants. One of the key advantages of the approach is that it avoids the computation of Pareto fronts in real-time environments. In addition, the approach can handle general objectives of different nature such as economic and regularization.

Piezoresistive effect in single-walled carbon nanotubes

This paper reports on the results of the theoretical investigation of the piezoresistive effect in single-walled carbon nanotubes of two structural modifications: arm-chair type and zig-zag type. The variation in the band gap of semiconducting nanotubes under the influence of the compressive and tensile deformations has been analyzed. The main quantitative characteristic of the piezoresistive effect—the longitudinal component of the elastic conductivity tensor—has been calculated, and its dependence on the diameter of semiconducting nanotubes has been shown. The variants of practical implementation of the effect under study have been proposed.

Press hardening — An innovative and challenging technology

In view of the growing demand for high-strength, press-hardened sheet metal components and the increasing need for energy and resource efficient process-chains, the optimization of the press hardening process chain is a complex, multi-layered and challenging task. The aim of the present paper is to show the potential for optimization in the press-hardening process chain and to demonstrate initial implementation variants.

Current controllers for devices of microplasma oxidation

Questions of the development of current controllers for microplasma oxidation devices with a wide set of functions are considered. Different variants of implementation of controllers based on a thyristor controlled rectifier and transistor power converter are presented. Mathematical modeling and investigation of operational modes of power units of controllers are performed. The results of testing the experimental samples are presented.

Dynamic selection of implementation variants of sequential iterated runge-kutta methods with tile size sampling (abstracts only)

This paper describes an efficient self-adaptive procedure for iterated Runge-Kutta (IRK) methods, a class of solution methods for initial value problems (IVPs) of ordinary differential equations (ODEs). IRK methods execute a potentially large number of discrete time steps to compute the solution of the IVP. The performance of an IRK solver may strongly depend on the specific characteristics of the given IVP and the hardware architecture on which the solver is executed. To address this problem, this paper applies dynamic auto-tuning to the sequential execution of IRK methods. Auto-tuning is a promising technique to avoid time consuming and extensive manual tuning. Our self-adaptive IRK solver utilizes the time-stepping nature of the IRK method. It selects the fastest implementation variant for the given IVP on the target architecture from a candidate pool during the first time steps. Then, the fastest implementation variant is used to compute all remaining time steps. The different implementation variants in the candidate pool have been developed by modifications of the loop structure of the basic algorithm. For those implementation variants that use loop tiling, we consider different tile sizes during the autotuning phase to further improve the performance of the selfadaptive IRK solver. Runtime experiments demonstrate the efficiency of the self-adaptive IRK solver for different IVPs on different hardware architectures.

Flow Radar Glyphs—Static Visualization of Unsteady Flow with Uncertainty

A new type of glyph is introduced to visualize unsteady flow with static images, allowing easier analysis of time-dependent phenomena compared to animated visualization. Adopting the visual metaphor of radar displays, this glyph represents flow directions by angles and time by radius in spherical coordinates. Dense seeding of flow radar glyphs on the flow domain naturally lends itself to multi-scale visualization: zoomed-out views show aggregated overviews, zooming-in enables detailed analysis of spatial and temporal characteristics. Uncertainty visualization is supported by extending the glyph to display possible ranges of flow directions. The paper focuses on 2D flow, but includes a discussion of 3D flow as well. Examples from CFD and the field of stochastic hydrogeology show that it is easy to discriminate regions of different spatiotemporal flow behavior and regions of different uncertainty variations in space and time. The examples also demonstrate that parameter studies can be analyzed because the glyph design facilitates comparative visualization. Finally, different variants of interactive GPU-accelerated implementations are discussed.

Using explicit platform descriptions to support programming of heterogeneous many-core systems

Heterogeneous many-core systems constitute a viable approach for coping with power constraints in modern computer architectures and can now be found across the whole computing landscape ranging from mobile devices, to desktop systems and servers, all the way to high-end supercomputers and large-scale data centers. While these systems promise to offer superior performance-power ratios, programming heterogeneous many-core architectures efficiently has been shown to be notoriously difficult. Programmers typically are forced to take into account a plethora of low-level architectural details and usually have to resort to a combination of different programming models within a single application. In this paper we propose a platform description language (PDL) that enables to capture key architectural patterns of commonly used heterogeneous computing systems. PDL architecture descriptions support both programmers and toolchains by providing platform-specific information in a well-defined and explicit manner. We have developed a prototype source-to-source compilation framework that utilizes PDL descriptors to transform sequential task-based programs with source code annotations into a form that is convenient for execution on heterogeneous many-core systems. Our framework relies on a component-based approach that accommodates for different implementation variants of tasks, customized for different parts of a heterogeneous platform, and utilizes an advanced runtime system for exploiting parallelism through dynamic task scheduling. We show various usage scenarios of our PDL and demonstrate the effectiveness of our framework for a commonly used scientific kernel and a financial application on different configurations of a state-of-the-art CPU/GPU system.

Optimized composition of performance‐aware parallel components

SUMMARYWe describe the principles of a novel framework for performance‐aware composition of sequential and explicitly parallel software components with implementation variants. Automatic composition results in a table‐driven implementation that, for each parallel call of a performance‐aware component, looks up the expected best implementation variant, processor allocation and schedule given the current problem, and processor group sizes. The dispatch tables are computed off‐line at component deployment time by an interleaved dynamic programming algorithm from time‐prediction meta‐code provided by the component supplier. Copyright © 2011 John Wiley & Sons, Ltd.

Supporting OpenMP on a multi-cluster embedded MPSoC

The ever-increasing complexity of MPSoCs is putting the production of software on the critical path in embedded system development. Several programming models and tools have been proposed in the recent past that aim to facilitate application development for embedded MPSoCs. OpenMP is a mature and easy-to-use standard for shared memory programming, which has recently been successfully adopted in embedded MPSoC programming as well. To achieve performance, however, it is necessary that the implementation of OpenMP constructs efficiently exploits the many peculiarities of MPSoC hardware, and that custom features are provided to the programmer to control it. In this paper we consider a representative template of a modern multi-cluster embedded MPSoC and present an extensive evaluation of the cost associated with supporting OpenMP on such a machine, investigating several implementation variants that are aware of the memory hierarchy and of the heterogeneous interconnection.

An efficient time-step-based self-adaptive algorithm for predictor–corrector methods of Runge–Kutta type

Finding an efficient implementation variant for the numerical solution of problems from computational science and engineering involves many implementation decisions that are strongly influenced by the specific hardware architecture. The complexity of these architectures makes it difficult to find the best implementation variant by manual tuning. For numerical solution methods from linear algebra, auto-tuning techniques based on a global search engine as they are used for ATLAS or FFTW can be used successfully. These techniques generate different implementation variants at installation time and select one of these implementation variants either at installation time or at runtime, before the computation starts. For some numerical methods, auto-tuning at installation time cannot be applied directly, since the best implementation variant may strongly depend on the specific numerical problem to be solved. An example is solution methods for initial value problems (IVPs) of ordinary differential equations (ODEs), where the coupling structure of the ODE system to be solved has a large influence on the efficient use of the memory hierarchy of the hardware architecture. In this context, it is important to use auto-tuning techniques at runtime, which is possible because of the time-stepping nature of ODE solvers. In this article, we present a sequential self-adaptive ODE solver that selects the best implementation variant from a candidate pool at runtime during the first time steps, i.e., the auto-tuning phase already contributes to the progress of the computation. The implementation variants differ in the loop structure and the data structures used to realize the numerical algorithm, a predictor–corrector (PC) iteration scheme with Runge–Kutta (RK) corrector considered here as an example. For those implementation variants in the candidate pool that use loop tiling to exploit the memory hierarchy of a given hardware platform we investigate the selection of tile sizes. The self-adaptive ODE solver combines empirical search with a model-based approach in order to reduce the search space of possible tile sizes. Runtime experiments demonstrate the efficiency of the self-adaptive solver for different IVPs across a range of problem sizes and on different hardware architectures.

Walking On Broken Mesh: Defect‐Tolerant Geodesic Distances and Parameterizations

AbstractEfficient methods to compute intrinsic distances and geodesic paths have been presented for various types of surface representations, most importantly polygon meshes. These meshes are usually assumed to be well‐structured and manifold. In practice, however, they often contain defects like holes, gaps, degeneracies, non‐manifold configurations – or they might even be just a soup of polygons. The task of repairing these defects is computationally complex and in many cases exhibits various ambiguities demanding tedious manual efforts. We present a computational framework that enables the computation of meaningful approximate intrinsic distances and geodesic paths on raw meshes in a way which is tolerant to such defects. Holes and gaps are bridged up to a user‐specified tolerance threshold such that distances can be computed plausibly even across multiple connected components of inconsistent meshes. Further, we show ways to locally parameterize a surface based on geodesic distance fields, easily facilitating the application of textures and decals on raw meshes. We do all this without explicitly repairing the input, thereby avoiding the costly additional efforts. In order to enable broad applicability we provide details on two implementation variants, one optimized for performance, the other optimized for memory efficiency. Using the presented framework many applications can readily be extended to deal with imperfect meshes. Since we abstract from the input applicability is not even limited to meshes, other representations can be handled as well.

ОценкА И управлЕниЕ качествоМ процессА разработкИ прОграммнОгО обеспечениЯ нА основЕ моделеЙ зрелостИ

We propose to formulate the problem of achieving the necessary level of maturity for the software process based on the selection among alternate variants of the process steps implementation under the resource constraints of the organization

Real-time object detection on CUDA

The aim of the research described in this article is to accelerate object detection in images and video sequences using graphics processors. It includes algorithmic modifications and adjustments of existing detectors, constructing variants of efficient implementations and evaluation comparing with efficient implementations on the CPUs. This article focuses on detection by statistical classifiers based on boosting. The implementation and the necessary algorithmic alterations are described, followed by experimental measurements of the created object detector and discussion of the results. The final solution outperforms the reference efficient CPU/SSE implementation, by approximately 6---8× for high-resolution videos using nVidia GeForce 9800GTX and Intel Core2 Duo E8200.

Computer Model of Megagauss Multilayer Quasi-Force-Free Magnet With Balanced End Parts

The choice of end parts shape and their numerical analysis are very important for quasi-force-free magnet design. Different variants of the magnet implementation are presented and corresponding dimensions limits and mechanical stresses are presented in the paper.

Generating broadband random Gaussian signals

General approaches to the problem of generating random Gaussian signals are considered, a variant of practical implementation of such a generator is proposed, some technological aspects of the formation of active device structures are discussed, and spectral characteristics of the output noise signal are presented. The technical solution is based upon the principle of additive formation of a Gaussian process as a result of the joint operation of a group of parallel connected pulsed signal sources of the microplasma type. The proposed devices were implemented as GaAs microchips with p-n structures fabricated by epitaxial-diffusion technology, on which a matrix relief of elementary noise sources was formed using the microlithography techniques.

Specific features of controlling laser systems for micromachining of moving carriers

One possible approach of controlling laser systems based on galvanometric scanners for precision micromachining of continuously moving materials is considered. A variant of implementation of the system with sensors of relative displacements of the material and real-time correction algorithms is demonstrated, which ensures the micromachining velocity close to the maximum possible value for these scanners. Experimental results of micromachining of polymer tapes are given.

Solving Constrained Total-variation Image Restoration and Reconstruction Problems via Alternating Direction Methods

In this paper, we study alternating direction methods for solving constrained total-variation image restoration and reconstruction problems. Alternating direction methods can be implementable variants of the classical augmented Lagrangian method for optimization problems with separable structures and linear constraints. The proposed framework allows us to solve problems of image restoration, impulse noise removal, inpainting, and image cartoon+texture decomposition. As the constrained model is employed, we need only to input the noise level, and the estimation of the regularization parameter is not required in these imaging problems. Experimental results for such imaging problems are presented to illustrate the effectiveness of the proposed method. We show that the alternating direction method is very efficient for solving image restoration and reconstruction problems.

An implementation variant of the polynomial finite difference method with orthogonal collocation and adjustable element length

The polynomial finite difference method, an easy-to-use variant of the finite difference method for the numerical solution of differential and differential–algebraic equations, has been recently presented [Wu, B., & White, R.E. (2004). Computers & Chemical Engineering, 28, 303–309]. In this work, it is shown that the polynomial finite difference method can be seen as a collocation method with finite elements of equal size with uniform distribution of collocation points within each element. We show that the same type of implementation can be improved if one uses orthogonal distribution of collocation points, without significantly affecting the computational effort. The suggested method is further improved with the use of Michelsen's technique for step-size adjustment to solve stiff differential equations with a semi-implicit third order method. Several examples that show improvements of one or two orders of magnitude of the proposed approach over the implementation by Wu and White are presented.

Simulation based verification of energy storage architectures for higher class tags supported by energy harvesting devices

Enhanced RFID tag technology especially in the UHF frequency range provides an extended functionality like high operating range and sensing and monitoring capabilities. Such complex functionality requires extended system structures including data acquisition units, real time clocks and active transmitters that cause a high energy consumption of the tag and require an on-board energy store (battery). Since the lifetime is a key parameter for the reliability of an RFID system, the energy budget of the higher class tag has to be as balanced as possible. This can be achieved by using energy harvesting devices as additional power supplies. The PowerTag 1 This project has been supported by Austrian government under the Grant number 811854. 1 project and thus this paper propose special energy storage structures, which interface energy harvesting devices and deal with their special requirements to be used with battery-driven higher class UHF RFID tags. Different implementation variants of such structures are compared by using accurate simulation models of various parts of the system. The results of the simulation are compared to provided manufacturer performance parameters of a state-of-the-art higher class UHF RFID system.

Fluorinated proton-conduction nafion-type membranes, the past and the future

Most of key decisions concerning the energetic safety problems, aimed to minimize climatic changes upon an increase in the energy consumption, diminish toxic discharges into the living environment, and save energy resources were formulated in the cooperation agreement between the European Community and the United States, signed on June 25, 2003, in Washington by the EC President R. Prodi, Greek Prime Minister K. Simitis, and United States President J. Bush [4]. The energy policy of the countries that signed the agreement was based on hydrogen energetics and use of fuel cells as the most optimal variants of implementation of stable energy supply systems.