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  • Open Access

    ARTICLE

    A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

    Zhaohui Xia1,3, Baichuan Gao3, Chen Yu2,*, Haotian Han3, Haobo Zhang3, Shuting Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1103-1137, 2024, DOI:10.32604/cmes.2023.029177

    Abstract This paper aims to solve large-scale and complex isogeometric topology optimization problems that consume significant computational resources. A novel isogeometric topology optimization method with a hybrid parallel strategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equation solving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency of CPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload between CPU and GPU. To illustrate the advantages of the proposed method, three benchmark examples are tested to verify the hybrid parallel strategy in this paper. The results… More > Graphic Abstract

    A Hybrid Parallel Strategy for Isogeometric Topology Optimization via CPU/GPU Heterogeneous Computing

  • Open Access

    ARTICLE

    A Novel Parallel Computing Confidentiality Scheme Based on Hindmarsh-Rose Model

    Jawad Ahmad1,*, Mimonah Al Qathrady2, Mohammed S. Alshehri3, Yazeed Yasin Ghadi4, Mujeeb Ur Rehman5, Syed Aziz Shah6

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1325-1341, 2023, DOI:10.32604/cmc.2023.040858

    Abstract Due to the inherent insecure nature of the Internet, it is crucial to ensure the secure transmission of image data over this network. Additionally, given the limitations of computers, it becomes even more important to employ efficient and fast image encryption techniques. While 1D chaotic maps offer a practical approach to real-time image encryption, their limited flexibility and increased vulnerability restrict their practical application. In this research, we have utilized a 3D Hindmarsh-Rose model to construct a secure cryptosystem. The randomness of the chaotic map is assessed through standard analysis. The proposed system enhances security by incorporating an increased number… More >

  • Open Access

    ARTICLE

    Enhanced Parallelized DNA-Coded Stream Cipher Based on Multiplayer Prisoners’ Dilemma

    Khaled M. Suwais*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2685-2704, 2023, DOI:10.32604/cmc.2023.036161

    Abstract Data encryption is essential in securing exchanged data between connected parties. Encryption is the process of transforming readable text into scrambled, unreadable text using secure keys. Stream ciphers are one type of an encryption algorithm that relies on only one key for decryption and as well as encryption. Many existing encryption algorithms are developed based on either a mathematical foundation or on other biological, social or physical behaviours. One technique is to utilise the behavioural aspects of game theory in a stream cipher. In this paper, we introduce an enhanced Deoxyribonucleic acid (DNA)-coded stream cipher based on an iterated n-player… More >

  • Open Access

    ARTICLE

    Implementation of OpenMP Parallelization of Rate-Dependent Ceramic Peridynamic Model

    Haoran Zhang1, Yaxun Liu2, Lisheng Liu2,*, Xin Lai2,*, Qiwen Liu2, Hai Mei2

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 195-217, 2022, DOI:10.32604/cmes.2022.020495

    Abstract A rate-dependent peridynamic ceramic model, considering the brittle tensile response, compressive plastic softening and strain-rate dependence, can accurately represent the dynamic response and crack propagation of ceramic materials. However, it also considers the strain-rate dependence and damage accumulation caused by compressive plastic softening during the compression stage, requiring more computational resources for the bond force evaluation and damage evolution. Herein, the OpenMP parallel optimization of the rate-dependent peridynamic ceramic model is investigated. Also, the modules that compute the interactions between material points and update damage index are vectorized and parallelized. Moreover, the numerical examples are carried out to simulate the… More >

  • Open Access

    ARTICLE

    A Parallel Computing Schema Based on IGA

    Jinggang Deng1,2, Bingquan Zuo1,2,*, Huixin Luo1,2, Weikang Xie1,2, Jiashu Yang1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 965-990, 2022, DOI:10.32604/cmes.2022.020631

    Abstract In this paper, a new computation scheme based on parallelization is proposed for Isogeometric analysis. The parallel computing is introduced to the whole progress of Isogeometric analysis. Firstly, with the help of the “tensorproduct” and “iso-parametric” feature, all the Gaussian integral points in particular element can be mapped to a global matrix using a transformation matrix that varies from element. Then the derivatives of Gauss integral points are computed in parallel, the results of which can be stored in a global matrix. And a middle layer is constructed to assemble the final stiffness matrices in parallel. The numerical example results… More >

  • Open Access

    ARTICLE

    Real-time Volume Preserving Constraints for Volumetric Model on GPU

    Hongly Va1, Min-Hyung Choi2, Min Hong3,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 831-848, 2022, DOI:10.32604/cmc.2022.029576

    Abstract This paper presents a parallel method for simulating real-time 3D deformable objects using the volume preservation mass-spring system method on tetrahedron meshes. In general, the conventional mass-spring system is manipulated as a force-driven method because it is fast, simple to implement, and the parameters can be controlled. However, the springs in traditional mass-spring system can be excessively elongated which cause severe stability and robustness issues that lead to shape restoring, simulation blow-up, and huge volume loss of the deformable object. In addition, traditional method that uses a serial process of the central processing unit (CPU) to solve the system in… More >

  • Open Access

    ARTICLE

    A GPU-Based Parallel Algorithm for 2D Large Deformation Contact Problems Using the Finite Particle Method

    Wei Wang1,2, Yanfeng Zheng1,3, Jingzhe Tang1, Chao Yang1, Yaozhi Luo1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 595-626, 2021, DOI:10.32604/cmes.2021.017321

    Abstract Large deformation contact problems generally involve highly nonlinear behaviors, which are very time-consuming and may lead to convergence issues. The finite particle method (FPM) effectively separates pure deformation from total motion in large deformation problems. In addition, the decoupled procedures of the FPM make it suitable for parallel computing, which may provide an approach to solve time-consuming issues. In this study, a graphics processing unit (GPU)-based parallel algorithm is proposed for two-dimensional large deformation contact problems. The fundamentals of the FPM for planar solids are first briefly introduced, including the equations of motion of particles and the internal forces of… More >

  • Open Access

    ARTICLE

    AAP4All: An Adaptive Auto Parallelization of Serial Code for HPC Systems

    M. Usman Ashraf1,*, Fathy Alburaei Eassa2, Leon J. Osterweil3, Aiiad Ahmad Albeshri2, Abdullah Algarni2, Iqra Ilyas4

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 615-639, 2021, DOI:10.32604/iasc.2021.019044

    Abstract High Performance Computing (HPC) technologies are emphasizing to increase the system performance across many disciplines. The primary challenge in HPC systems is how to achieve massive performance by minimum power consumption. However, the modern HPC systems are configured by adding the powerful and energy efficient multi-cores/many-cores parallel computing devices such as GPUs, MIC, and FPGA etc. Due to increasing the complexity of one chip many-cores/multi-cores systems, only well-balanced and optimized parallel programming technique is the solution to provide substantial increase in performance under power consumption limitations. Conventionally, the researchers face various barriers while parallelizing their serial code because they don’t… More >

  • Open Access

    ARTICLE

    BFS Parallel Algorithm Based on Sunway TaihuLight

    Yang Zhou1, Jinhui He1, Hao Yang1,2,*

    Journal of New Media, Vol.3, No.2, pp. 63-72, 2021, DOI:10.32604/jnm.2021.018829

    Abstract In recent years, more and more attention has been paid to the research and application of graph structure. As the most typical representative of graph structure algorithm, breadth first search algorithm is widely used in many fields. However, the performance of traditional serial breadth first search (BFS) algorithm is often very low in specific areas, especially in large-scale graph structure traversal. However, it is very common to deal with large-scale graph structure in scientific research. At the same time, the computing performance of supercomputer has also made great progress. China’s self-developed supercomputer system Sunway TaihuLight (SW) has won the top… More >

  • Open Access

    ARTICLE

    Human Activity Recognition Based on Parallel Approximation Kernel K-Means Algorithm

    Ahmed A. M. Jamel1,∗, Bahriye Akay2,†

    Computer Systems Science and Engineering, Vol.35, No.6, pp. 441-456, 2020, DOI:10.32604/csse.2020.35.441

    Abstract Recently, owing to the capability of mobile and wearable devices to sense daily human activity, human activity recognition (HAR) datasets have become a large-scale data resource. Due to the heterogeneity and nonlinearly separable nature of the data recorded by these sensors, the datasets generated require special techniques to accurately predict human activity and mitigate the considerable heterogeneity. Consequently, classic clustering algorithms do not work well with these data. Hence, kernelization, which converts the data into a new feature vector representation, is performed on nonlinearly separable data. This study aims to present a robust method to perform HAR data clustering to… More >

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