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 >

Haishan Lu, Shuguang Gong^*, Jianping Zhang, Guilan Xie, Shuohui Yin

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1151-1178, 2021, DOI:10.32604/cmes.2021.016165

Abstract We proposed an improved graphics processing unit (GPU) acceleration approach for three-dimensional structural topology optimization using the element-free Galerkin (EFG) method. This method can effectively eliminate the race condition under parallelization. We established a structural topology optimization model by combining the EFG method and the solid isotropic microstructures with penalization model. We explored the GPU parallel algorithm of assembling stiffness matrix, solving discrete equation, analyzing sensitivity, and updating design variables in detail. We also proposed a node pair-wise method for assembling the stiffness matrix and a node-wise method for sensitivity analysis to eliminate race conditions during the parallelization. Furthermore, we… More >

Ke Song^1,*, Paul Liu², Dongquan Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1133-1150, 2021, DOI:10.32604/cmes.2021.016008

Abstract A novel beamforming algorithm named Delay Multiply and Sum (DMAS), which excels at enhancing the resolution and contrast of ultrasonic image, has recently been proposed. However, there are nested loops in this algorithm, so the calculation complexity is higher compared to the Delay and Sum (DAS) beamformer which is widely used in industry. Thus, we proposed a simple vector-based method to lower its complexity. The key point is to transform the nested loops into several vector operations, which can be efficiently implemented on many parallel platforms, such as Graphics Processing Units (GPUs), and multi-core Central Processing Units (CPUs). Consequently, we… More >

Xinyue Chu¹, Jiaquan Gao^1,*, Bo Sheng²

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

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 (A^Tx), 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 the perspective of the… More >

Xu Li¹, Ying Yan², Shuai Shao³, Shunying Ji^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 645-671, 2021, DOI:10.32604/cmes.2021.013674

Abstract Considering the interaction between a sleeper, ballast layer, and substructure, a three-dimensional coupled discrete-finite element method for a ballasted railway track is proposed in this study. Ballast granules with irregular shapes are constructed using a clump model using the discrete element method. Meanwhile, concrete sleepers, embankments, and foundations are modelled using 20-node hexahedron solid elements using the finite element method. To improve computational efficiency, a GPU-based (Graphics Processing Unit) parallel framework is applied in the discrete element simulation. Additionally, an algorithm containing contact search and transfer parameters at the contact interface of discrete particles and finite elements is developed in… More >

Syed Mustajar Ahmad Shah¹, Hongwei Ge^1,*, 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

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 matrix of graphs, a new… More >

Majdi K. Qabalin¹, Zaid A. Arida², Omar A. Saraereh³, Falin Wu^4,*, Imran Khan⁵, Peerapong Uthansakul⁶, Moath Alsafasfeh⁷

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

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. To overcome the shortcomings of… More >

G. Ravikanth^1,∗, K. V. N. Sunitha^2,†, B. Eswara Reddy³

Computer Systems Science and Engineering, Vol.35, No.5, pp. 385-393, 2020

Abstract Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand of upgrading the view of… More >

Sa’ed Abed^∗, Mohammed H. Ali^†, Mohammad Al-Shayeji^‡

Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically. Thus, increased processing power is… More >