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Bilevel and parallel programing-Based Operability Approaches for Process Intensification and Modularity

AICHE JOURNAL 2018年第8期64卷 3042-3054页

作者： Carrasco, Juan C. Lima, Fernando V. West Virginia Univ Dept Chem & Biomed Engn Morgantown WV 26506 USA

Process operability emerged in the last decades as a powerful tool for the design and control of chemical processes. Recent efforts in operability have been focused on the calculation of the desired input set for process design and intensification of natural gas utilization applications described by nonlinear models. However, there is still a gap in terms of problem dimensionality that nonlinear operability methods can handle. To fill this gap, in this article, the incorporation of bilevel and parallel programing approaches into classical process operability concepts is discussed. Results on the implementation of the proposed method show a reduction in computational time up to two orders of magnitude, when compared to the original results without parallelization. These results could be extrapolated for use in a supercomputer as presented in the computational time analysis performed. In terms of intensification, the proposed approach can produce a natural gas combined cycle plant modular design with a dramatic reduction in size, from the original 400 to 0.11 MW, while still keeping the high net plant efficiency. This approach thus provides a computationally efficient framework for process intensification of high-dimensional nonlinear energy systems toward modularity. The proposed approach also enables the verification of a modular design and conditions that can be obtained according to economic and physical constraints associated with a specific natural gas well production. (C) 2018 American Institute of Chemical Engineers

关键词： operability bilevel optimization parallel programing process intensification modularity

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A parallel Multibit programing Scheme With High Precision for RRAM-Based Neuromorphic Systems

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IEEE TRANSACTIONS ON ELECTRON DEVICES 2020年第5期67卷 2213-2217页

作者： Chen, Junren Wu, Huaqiang Gao, Bin Tang, Jianshi Hu, Xiaobo Sharon Qian, He Tsinghua Univ Innovat Ctr Future Chips ICFC Inst Microelect Beijing 100084 Peoples R China Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

Resistive random access memory (RRAM) has been extensively studied as a promising candidate for neuromorphic computing. So far, high-precision multibit programing of RRAM for neuromorphic systems is done cell-by-cell, which can be very time-consuming. This brief demonstrates a row-by-row parallel program-verify scheme on a fabricated 160-Kb RRAM array using the incremental gate voltage programing (IGVP) method. Statistical analysis indicates that the optimal conductance tuning step size can accelerate the programing process and improve the success rate. Also, for the first time, the fundamental relations between programing success rate, critical path, and parallel efficiency for parallel program-verify methodology on the RRAM array are systematically studied. Moreover, a software-comparable recognition accuracy with only <0.3% accuracy loss is experimentally achieved for MNIST data set classification utilizing the proposed parallel program-verify scheme.

关键词： 1-transistor-1-RRAM(1T1R) array multibit neuromorphic system parallel programing program-verify resistive random access memory (RRAM)

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Cellular automata model of anodization

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JOURNAL OF COMPUTATIONAL SCIENCE 2015年第Nov.期11卷 309-316页

作者： Bartosik, Lukasz Stafiej, Janusz Di Caprio, Dung Polish Acad Sci Inst Phys Chem Warsaw Poland Cardinal Stefan Wyszynski Univ Dept Math & Nat Sci Warsaw Poland PSL Res Univ Chim ParisTech CNRS Inst Rech Chim Paris F-75005 Paris France

We present a cellular automata model to simulate with a parallelized code nanostructured alumina formation during anodization. The model is based on the Field Assisted Dissolution approach for anodization. The parallel code for model simulation is run on Nvidia Tesla GPU cards. We verify that the parallel algorithm yields correct analytical results for the simple exclusion diffusion between emitting and absorbing walls in 3D. We identify the model parameters that have a strong impact on the nanostructures obtained in simulations and present the diagram of prevalence of these structures. We also simulate in our model the so called "two step anodization" and find an agreement with experimental findings. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Anodization Cellular automata parallel programing Aluminum oxide growth

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On the Evaluation of Different High-Performance Computing Platforms for Hyperspectral Imaging: An OpenCL-Based Approach

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2017年第11期10卷 4879-4897页

作者： Guerra, Raul Martel, Ernestina Khan, Jehandad Lopez, Sebastian Athanas, Peter Sarmiento, Roberto Inst Appl Microelect Integrated Syst Design Div Las Palmas Gran Canaria 35017 Spain Univ Las Palmas Gran Canaria Inst Univ Microelect Aplicada Las Palmas Gran Canaria 35017 Spain Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA 24061 USA

Hyperspectral imaging systems are a powerful tool for obtaining surface information in many different spectral channels that can be used in many different applications. Nevertheless, the huge amount of information provided by hyperspectral images also has a downside, since it has to be processed and analyzed. For such purpose, parallel hardware devices, such as field-programmable gate arrays (FPGAs) and graphic processing units (GPUs), are typically used, especially for hyperspectral imaging applications under real-time constraints. However, developing hardware applications typically requires expertise in the specific targeted device, as well as in the tools and methodologies that can be used to perform the implementation of the desired algorithms in that device. In this scenario, the Open Computing Language (OpenCL) emerges as a very interesting solution in which a single high-level language can be used to efficiently develop applications in multiple and different hardware devices. In this work, the parallel Fast Algorithm for Linearly Unmixing Hyperspectral Images (pFUN) has been implemented in two different NVIDIA GPUs, the GeForce GTX 980 and the Tesla K40c, using OpenCL. The obtained results are compared with the results provided by the previously developed NVIDIA CUDA implementation of the pFUN algorithm for the same GPU devices for comparing the efficiency of OpenCL against a more specific synthesis design language for the targeted hardware devices, such as CUDA is for NVIDIA GPUs. Moreover, the FUN algorithm has also been implemented into a Bitware Stratix V Altera FPGA, using OpenCL, for comparing the results that can be obtained using OpenCL when targeting different devices and architectures. The obtained results demonstrate the suitability of the followed methodology in the sense that it allows the achievement of efficient FPGA and GPU implementations able to cope with the stringent requirements imposed by hyperspectral imaging systems.

关键词： CUDA field-programmable gate array (FPGA) graphic processing unit (GPU) high-performance computing hyperspectral imaging hyperspectral unmixing open computing language (openCL) parallel programing

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Hypercube Based Clusters in Cloud Computing

Hypercube Based Clusters in Cloud Computing

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World Automation Congress (WAC)

作者： Sahba, Amin Prevost, John J. Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA

ISBN: (纸本)9781889335513

High performance computing (HPC) means the aggregation of computational power to increase the ability of processing large problems in science, engineering, and business. HPC on the cloud allows performing on demand HPC tasks by high performance clusters in a cloud environment. The connection structure of the nodes in HPC clusters should provide fast internode communication. It is important that scalability is preserved as well. This paper proposes a hypercube topology for connecting the nodes in an HPC cluster that facilitates fast communications between nodes. In addition, the proposed hypercube topology provides the ability to scale, which is needed for high performance computing on the cloud.

关键词： Cloud computing high performance computing hypercube cluster parallel programing

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PICA: Multi-Population Implementation of parallel Imperialist Competitive Algorithms 24

PICA: Multi-Population Implementation of Parallel Imperialis...

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24th Euromicro International Conference on parallel, Distributed, and Network-Based Processing (PDP)

作者： Majd, Amin Lotfi, Shahriar Sahebi, Golnaz Daneshtalab, Masoud Plosila, Juha Univ Turku Dept Informat Technol Turku Finland Univ Tabri Dept Comp Sci Tabriz Iran Royal Inst Technol KTH Stockholm Sweden

ISBN: (纸本)9781467387767

The importance of optimization and NP problems solving cannot be over emphasized. The usefulness and popularity of evolutionary computing methods are also well established. There are various types of evolutionary methods that arc mostly sequential, and some others have parallel implementation. We propose a method to parallelize Imperialist Competitive Algorithm (Multi-Population). The algorithm has been implemented with MPI on two platforms and have tested our algorithms on a shared- memory and message passing architecture. An outstanding performance is obtained, which indicates that the method is efficient concern to speed and accuracy. In the second step, the proposed algorithm is compared with a set of existing well known parallel algorithms and is indicated that it obtains more accurate solutions in a lower time.

关键词： optimization evolutionary computing parallel approaches ICA parallel programing multi-population super linear performance

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Classification Of Human Facial Expressions For Emotion Recognition Using A Distributed Computer System 5

Classification Of Human Facial Expressions For Emotion Recog...

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5th International Conference on Computer Science and Engineering (UBMK)

作者： Korkmaz, Timucin Erol, Hamza Mersin Univ Grad Sch Nat & Appl Sci Dept Comp Engn Mersin Turkey Mersin Univ Engn Fac Dept Comp Engn Mersin Turkey

ISBN: (纸本)9781728175652

A computer system was developed to classify human facial expressions for emotion recognition using a distributed computer architecture within the scope of big data. Computers with normal standards and features were used in the distributed computer architecture. Necessary system software for the distributed computer architecture was established and mutual communication protocols were provided between the computers and databases in the computer network. Visual C# parallel programming was used as the software language on the distributed computer architecture. In the software prepared, face image files were processed and threads were created. The threads created later were processed in the processors of the computers. The threads were run on the processors in the distributed computer system, and facial expressions were classified for emotion recognition. In the distributed computer architecture: the number of image files, the volume of big data and the load of the threads to be processed arc taken into account;and databases and parallel programming were used and the classification of human face images was performed. Emotion analysis methods and facial expression recognition techniques were used in the classification process. The distributed computer system is in low cost and high processing speed. With the distributed computer system architecture, big data analytics has become convenient and feasible.

关键词： Big data Distributed System Emotion analysis Image classification parallel programing Face expression recognition

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parallel Artificial Bee Colony Algorithm For Traveling Salesman Problem

Parallel Artificial Bee Colony Algorithm For Traveling Sales...

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22nd IEEE Signal Processing and Communications Applications Conference (SIU)

作者： Akay, Rustu Basturk, Alper Erciyes Univ Fen Bilimleri Enstitusu Kayseri Turkey Erciyes Univ Bilgisayar Muhendisligi Bolumu Kayseri Turkey

ISBN: (纸本)9781479948741

In this study, we proposed a parallel implementation of the combinatorial type artificial bee colony algorithm which has an efficient neighbor production mechanism. Running time and performance tests of the proposed parallel model were carried on the traveling salesmen problem. Results show that parallel artificial bee colony algorithm decreases the running time due to exploiting the computational power of parallel computing systems. Beside, better quality solutions are obtained compared to the reproduction methods of the genetic algorithm.

关键词： parallel programing artificial bee colony algorithm traveling salesmen problem

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Implementation of the image super-resolution DWT based algorithm on Raspberry Pi platform for real-time applications

Implementation of the image super-resolution DWT based algor...

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Conference on Real-Time Processing of Image, Depth, and Video Information

作者： Osorno-Ortiz, Raul J. Ponomaryov, Volodymyr, I Reyes-Reyes, Rogelio Cruz-Ramos, Clara Garcia-Salgado, Beatriz P. Sadovnychiy, Sergiy Inst Politecn Nacl ESIME Culhuacan Ciudad De Mexico Mexico Inst Mexicano Petr Ciudad De Mexico Mexico

ISBN: (纸本)9781510673199;9781510673182

Super resolution (SR) is a technique designed for increasing the spatial resolution in an image from a low resolution (LR) to high resolution (HR) size. SR technology has had a considerable demand in a wide variety of applications to recover HR images, such as medicine, engineering, computer vision, pattern recognition and video production, etc. In contrast to interpolation-based algorithms that often introduce distortions or irregular borders, this study proposes an implementation that can preserve the edges and fine details of an original image through the computation of the wavelet decomposition. Different Discrete Wavelet Transform (DWT) families such as: Daubechies, Symlet, and Coiflet were evaluated. The proposed system was implemented on a Raspberry Pi 4 model B, an embedded device, to get around the PC's mobility limitations, making it possible to create an in-expensive and energy- efficient SR system, reducing their complexity in realtime applications. To investigate the visual performance, SR images have been analysed in subjective matter via human perception view, guaranteeing good perception for the images of different nature from three different datasets such as FullHD (DIV2K), medical (Raabin WBC), and remote sensing (Sentinel- 1). The experimental results of designed implementations appear to demonstrate good performance in commonly used objective criteria: execution time, SSIM, and PSNR (0.742 sec., 0.9164, and 38.72 dB), respectively for images with a super resolution size of 1356 x 2040 pixels.

关键词： Super resolution Discrete Wavelet Transform (DWT) parallel programing Raspberry Pi real-time processing

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Fast Oil Paint Image Filter Algorithm: Optimization at overlapped sub-pixel

Fast Oil Paint Image Filter Algorithm: Optimization at overl...

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Int Conference Adv Elect Comp Commun ICAECC

作者： Mukherjee, Siddhartha Chudgar, Haresh S. Samsung R&D Inst DMC R&D Ctr Bangalore Karnataka India

ISBN: (纸本)9781479954964

Fast Oil Paint Image filter is a performance optimized oil paint algorithm. Current oil paint algorithms are CPU intensive and take a long time to produce the output;further the time taken increases exponentially with increasing quality. One of the main causes is re-computation. The proposed algorithm significantly reduces re-computation reducing the processing time by approximately 86%. The research also evaluates the algorithm using the parallel programming approach.

关键词： Image Filters Colour Image Processing Spatial filtering Oil Paint parallel programing

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