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  • Open Access

    ARTICLE

    Efficient Concurrent L1-Minimization Solvers on GPUs

    Xinyue Chu1, Jiaquan Gao1,*, Bo Sheng2

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 305-320, 2021, DOI:10.32604/csse.2021.017144 - 19 May 2021

    Abstract Given that the concurrent L1-minimization (L1-min) problem is often required in some real applications, we investigate how to solve it in parallel on GPUs in this paper. First, we propose a novel self-adaptive warp implementation of the matrix-vector multiplication (Ax) and a novel self-adaptive thread implementation of the matrix-vector multiplication (ATx), respectively, on the GPU. The vector-operation and inner-product decision trees are adopted to choose the optimal vector-operation and inner-product kernels for vectors of any size. Second, based on the above proposed kernels, the iterative shrinkage-thresholding algorithm is utilized to present two concurrent L1-min solvers from More >

  • Open Access

    ARTICLE

    A Quantum Spatial Graph Convolutional Network for Text Classification

    Syed Mustajar Ahmad Shah1, Hongwei Ge1,*, Sami Ahmed Haider2, Muhammad Irshad3, Sohail M. Noman4, Jehangir Arshad5, Asfandeyar Ahmad6, Talha Younas7

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 369-382, 2021, DOI:10.32604/csse.2021.014234 - 05 January 2021

    Abstract The data generated from non-Euclidean domains and its graphical representation (with complex-relationship object interdependence) applications has observed an exponential growth. The sophistication of graph data has posed consequential obstacles to the existing machine learning algorithms. In this study, we have considered a revamped version of a semi-supervised learning algorithm for graph-structured data to address the issue of expanding deep learning approaches to represent the graph data. Additionally, the quantum information theory has been applied through Graph Neural Networks (GNNs) to generate Riemannian metrics in closed-form of several graph layers. In further, to pre-process the adjacency… More >

  • Open Access

    ARTICLE

    An Improved Dictionary Cracking Scheme Based on Multiple GPUs for Wi-Fi Network

    Majdi K. Qabalin1, Zaid A. Arida2, Omar A. Saraereh3, Falin Wu4,*, Imran Khan5, Peerapong Uthansakul6, Moath Alsafasfeh7

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2957-2972, 2021, DOI:10.32604/cmc.2021.013951 - 28 December 2020

    Abstract The Internet has penetrated all aspects of human society and has promoted social progress. Cyber-crimes in many forms are commonplace and are dangerous to society and national security. Cybersecurity has become a major concern for citizens and governments. The Internet functions and software applications play a vital role in cybersecurity research and practice. Most of the cyber-attacks are based on exploits in system or application software. It is of utmost urgency to investigate software security problems. The demand for Wi-Fi applications is proliferating but the security problem is growing, requiring an optimal solution from researchers.… More >

  • Open Access

    ARTICLE

    Cracking of WPA & WPA2 Using GPUs and Rule‐based Method

    Tien‐Ho Chang1, Chia‐Mei Chen2, Han‐Wei Hsiao3, Gu‐Hsin Lai4

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 183-192, 2019, DOI:10.31209/2018.100000054

    Abstract Wi-Fi Protected Access (WPA) and Wi-Fi Protected Access II (WPA2) are two security protocols developed by the Wi-Fi Alliance to secure wireless computer networks. The prevailing usage of GPUs improves the brute force attacks and cryptanalysis on access points of the wireless networks. It is time-consuming for the cryptanalysis with the huge total combinations of 9563 max. Now, it is the turning point that the leap progress of GPUs makes the Wi-Fi cryptanalysis much more efficient than before. In this research, we proposed a rule-based password cracking scheme without dictionary files which improves the efficiency More >

  • Open Access

    ABSTRACT

    Simulations of Core Collapse Supernova Explosion on PEZY-SC Processors and GPUs

    Hideo Matsufuru1,*, Kohsuke Sumiyoshi2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.4, pp. 90-90, 2019, DOI:10.32604/icces.2019.05390

    Abstract The core collapse supernovae are one of key phenomena to understand the history of the Universe and the origin of heavy elements. To understand their explosion mechanism, large scale numerical simulations are essential that require to solve a multi-physics system described by coupled equations of hydrodynamics and neutrino-radiation transfer in multidimensions. Since the neutrino transfer is governed by the Boltzmann equation in six-dimensional space, necessary computational resource rapidly increases as the number of grids in simulations grows. So far numerical studies have been performed mostly on massively parallel computers and only a few studies have… More >

  • Open Access

    ARTICLE

    Comparison and Performance Analysis of Multiple CPU/GPU Computing Systems – Resin Infusion Flow Modeling Application

    R.H. Haney1, R.V. Mohan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.95, No.5, pp. 431-452, 2013, DOI:10.3970/cmes.2013.095.431

    Abstract The use of Graphics Processing Units (GPUs) as co-processors for single CPU/GPU computing systems has become pronounced in high performance computing research, however the solution of truly large scale computationally intensive problems require the utilization of multiple computing nodes. Multiple CPU/GPU computing systems bring new complexities to the observed performance of computationally intensive applications, the more salient of which is the cost of local CPU-GPU host and intra-nodal communication. This paper compares and analyzes the performance of a computationally intensive application represented by resin infusion flow during liquid composite molding process for the manufacture of… More >

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