Zhaohui Xia^1,3, Baichuan Gao³, Chen Yu^2,*, 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

Jawad Ahmad^1,*, 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 >

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 >

Haoran Zhang¹, Yaxun Liu², Lisheng Liu^2,*, Xin Lai^2,*, 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 >

Jinggang Deng^1,2, Bingquan Zuo^1,2,*, Huixin Luo^1,2, Weikang Xie^1,2, Jiashu Yang^1,2

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 >

Hongly Va¹, Min-Hyung Choi², Min Hong^3,*

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 >

Wei Wang^1,2, Yanfeng Zheng^1,3, Jingzhe Tang¹, Chao Yang¹, Yaozhi Luo^1,*

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 >

M. Usman Ashraf^1,*, 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 >

Yang Zhou¹, Jinhui He¹, Hao Yang^1,2,*

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 >

Ahmed A. M. Jamel^1,∗, Bahriye Akay^2,†

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 >