Analysis on intersections between fractures by parallel computation

The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush.Intersection analysis,which identifies all pairs of intersected fractures(the basic components composing the connectivity of a network),is one of its crucial procedures.This paper attempts to improve intersection analysis through parallel computing.Considering a seamless interfacing with other procedures in modeling,two algorithms are designed and presented,of which one is a completely independent parallel procedure with some redundant computations and the other is an optimized version with reduced redundancy.A numerical study indicates that both of the algorithms are practical and can significantly improve the computational performance of intersection analysis for large-scale simulations.Moreover,the preferred application conditions for the two algorithms are also discussed.

Parallelized Implementation of the Finite Particle Method for Explicit Dynamics in GPU

As a novel kind of particle method for explicit dynamics,the finite particle method(FPM)does not require the formation or solution of global matrices,and the evaluations of the element equivalent forces and particle displacements are decoupled in nature,thus making this method suitable for parallelization.The FPM also requires an acceleration strategy to overcome the heavy computational burden of its explicit framework for time-dependent dynamic analysis.To this end,a GPU-accelerated parallel strategy for the FPM is proposed in this paper.By taking advantage of the independence of each step of the FPM workflow,a generic parallelized computational framework for multiple types of analysis is established.Using the Compute Unified Device Architecture(CUDA),the GPU implementations of the main tasks of the FPM,such as evaluating and assembling the element equivalent forces and solving the kinematic equations for particles,are elaborated through careful thread management and memory optimization.Performance tests show that speedup ratios of 8,25 and 48 are achieved for beams,hexahedral solids and triangular shells,respectively.For examples consisting of explicit dynamic analyses of shells and solids,comparisons with Abaqus using 1 to 8 CPU cores validate the accuracy of the results and demonstrate a maximum speed improvement of a factor of 11.2.

A UNIVERSAL ALGORITHM FOR PARALLEL CRC COMPUTATION AND ITS IMPLEMENTATION

Derived from a proposed universal mathematical expression, this paper investigates a novel algo-rithm for parallel Cyclic Redundancy Check (CRC) computation, which is an iterative algorithm to update the check-bit sequence step by step and suits to various argument selections of CRC computation. The algorithm proposed is quite suitable for hardware implementation. The simulation implementation and performance analysis suggest that it could efficiently speed up the computation compared with the conventional ones. The algorithm is implemented in hardware at as high as 21Gbps, and its usefulness in high-speed CRC computa-tions is implied, such as Asynchronous Transfer Mode (ATM) networks and 10G Ethernet.

Parallel computation of unified finite-difference time-domain for underwater sound scattering

In this work, we treat scattering objects, water, surface and bottom in a truly unified manner in a parallel finitedifference time-domain （FDTD） scheme, which is suitable for distributed parallel computing in a message passing interface （MPI） programming environment. The algorithm is implemented on a cluster-based high performance computer system. Parallel computation is performed with different division methods in 2D and 3D situations. Based on analysis of main factors affecting the speedup rate and parallel efficiency, data communication is reduced by selecting a suitable scheme of task division. A desirable scheme is recommended, giving a higher speedup rate and better efficiency. The results indicate that the unified parallel FDTD algorithm provides a solution to the numerical computation of acoustic scattering.

Parallel Computation of Shallow-water Model on Workstations Cluster

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Development of high performance casting analysis software by coupled parallel computation

Up to now,so much casting analysis software has been continuing to develop the new access way to real casting processes. Those include the melt flow analysis,heat transfer analysis for solidification calculation,mechanical property predictions and microstructure predictions. These trials were successful to obtain the ideal results comparing with real situations,so that CAE technologies became inevitable to design or develop new casting processes. But for manufacturing fields,CAE technologies are not so frequently being used because of their difficulties in using the software or insufficient computing performances. To introduce CAE technologies to manufacturing field,the high performance analysis is essential to shorten the gap between product designing time and prototyping time. The software code optimization can be helpful,but it is not enough,because the codes developed by software experts are already optimized enough. As an alternative proposal for high performance computations,the parallel computation technologies are eagerly being applied to CAE technologies to make the analysis time shorter. In this research,SMP (Shared Memory Processing) and MPI (Message Passing Interface) (1) methods for parallelization were applied to commercial software "Z-Cast" to calculate the casting processes. In the code parallelizing processes,the network stabilization,core optimization were also carried out under Microsoft Windows platform and their performances and results were compared with those of normal linear analysis codes.

Preconditioned method in parallel computation

The grid equations in decomposed domain by parallel computation are soled, and a method of local orthogonalization to solve the large-scaled numerical computation is presented. It constructs preconditioned iteration matrix by the combination of predigesting LU decomposition and local orthogonalization, and the convergence of solution is proved. Indicated from the example, this algorithm can increase the rate of computation efficiently and it is quite stable.

Energy-efficient task allocation for reliable parallel computation of cluster-based wireless sensor network in edge computing

To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel computation.To achieve highly reliable parallel computation for wireless sensor network,the network's lifetime needs to be extended.Therefore,a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network.This paper proposes a task model and a cluster-based WSN model in edge computing.In our model,different tasks require different types of resources and different sensors provide different types of resources,so our model is heterogeneous,which makes the model more practical.Then we propose a task allocation algorithm that combines the Genetic Algorithm(GA)and the Ant Colony Optimization(ACO)algorithm.The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended.The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.

Towards sparse matrix operations:graph database approach for power grid computation

The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion ability.Native graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing tasks.However,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power grids.In this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the graph.Based on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,etc.Specifically,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix computation.Based on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph database.It promotes the efficiency of PIoT when handling multi-source heterogeneous data.An comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB baselines.The results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations.

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

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 prisoner’s dilemma paradigm.Our main goal is to contribute to adding more layers of randomness to the behaviour of the keystream generation process;these layers are inspired by the behaviour of multiple players playing a prisoner’s dilemma game.We implement parallelism to compensate for the additional processing time that may result fromadding these extra layers of randomness.The results show that our enhanced design passes the statistical tests and achieves an encryption throughput of about 1,877 Mbit/s,which makes it a feasible secure stream cipher.

Combination Method for Parallel Computation in ODEs

In this paper, a 3rd order combination method with three processes and a 4th order combination method with five processes for solving ODEs are discussed. These methods are the Runge-Kutta method combined with a linear multistep method, which overcomes the defect of the 3rd order parallel Runge-Kutta method discussed in [1].

Optimizing photoacoustic image reconstruction using cross-platform parallel computation

Three-dimensional(3D)image reconstruction involves the computations of an extensive amount of data that leads to tremendous processing time.Therefore,optimization is crucially needed to improve the performance and efficiency.With the widespread use of graphics processing units(GPU),parallel computing is transforming this arduous reconstruction process for numerous imaging modalities,and photoacoustic computed tomography(PACT)is not an exception.Existing works have investigated GPU-based optimization on photoacoustic microscopy(PAM)and PACT reconstruction using compute unified device architecture(CUDA)on either C++or MATLAB only.However,our study is the first that uses cross-platform GPU computation.It maintains the simplicity of MATLAB,while improves the speed through CUDA/C++−based MATLAB converted functions called MEXCUDA.Compared to a purely MATLAB with GPU approach,our cross-platform method improves the speed five times.Because MATLAB is widely used in PAM and PACT,this study will open up new avenues for photoacoustic image reconstruction and relevant real-time imaging applications.

Parallel Computation of Fourier Transform on Distributed Memory Computer System

Multicomputer systems(distributed memory computer systems) are becoming more and more popular and will be wildly used in scientific researches. In this paper, we present a parallel algorithm of Fourier Transform of a vector of complex numbers on multicomputer system and give its computing times and its speedup in parallel environment supported by EXPRESS system on the multicomputer system which consists of four SGI workstations. Our analysis shows that the results is ideal and this scheme is suitable to multicomputer systems.

A Class of Stable Difference Schemes For Linear Elliptic PDEs And Their Asynchronous Parallel Computation

This paper improves and generalizes the two difference schemes presented in paper [1] and gives a new difference scheme for second order linear elliptic partial differential equations, its difference matrix is a matrix and because of the stability of the M-matrix, it is convergent by the asynchronous iterative method on multiprocessors. Then this paper gives a class of differeifce schemes for linear elliptic PDEs so that their difference matrixes are all M-matrixes and their asynchronous parallel computation are convergent.

Realistic Efficiency Evaluations for Parallel Computations under Workstation Cluster

In recent years, high performance scientific computing under workstation cluster connected by local area network is becoming a hot point. Owing to both the longer latency and the higher overhead for protocol processing compared with the powerful single workstation capacity, it is becoming severe important to keep balance not only for numerical load but also for communication load, and to overlap communications with computations while parallel computing. Hence,our efficiency evaluation rules must discover these capacities of a given parallel algorithm in order to optimize the existed algorithm to attain its highest parallel efficiency. The traditional efficiency evaluation rules can not succeed in this work any more. Fortunately, thanks to Culler's detail discuss in LogP model about interconnection networks for MPP systems, we present a system of efficiency evaluation rules for parallel computations under workstation cluster with PVM3.0 parallel software framework in this paper. These rules can satisfy above acquirements successfully. At last, two typical synchronous,and asynchronous applications are designed to verify the validity of these rules under 4 SGIs workstations cluster connected by Ethernet.

A Parallel Computational Scheme on Hybrid Methods

Based on the efficient hybrid methods for solving initial value problems of stiff ODEs, this paper derives a parallel scheme that can be used to solve the problems on parallel computers with N processors, and discusses the iteratively B-convergence of the Newton iterative process, finally, the paper provides some numberical results which show that the parallel scheme is highly efficient as N is not too large.

Implementation Study of Dynamic Load Balancing Algorithm of Parallel Tree Computation on Clusters of Heterogeneous Workstation

The rapid growth of interconnected high performance workstations has produced a new computing paradigm called clustered of workstations computing. In these systems load balance problem is a serious impediment to achieve good performance. The main concern of this paper is the implementation of dynamic load balancing algorithm, asynchronous Round Robin (ARR), for balancing workload of parallel tree computation depth-first-search algorithm on Cluster of Heterogeneous Workstations (COW) Many algorithms in artificial intelligence and other areas of computer science are based on depth first search in implicitty defined trees. For these algorithms a load-balancing scheme is required, which is able to evenly distribute parts of an irregularly shaped tree over the workstations with minimal interprocessor communication and without prior knowledge of the tree’s shape. For the (ARR) algorithm only minimal interprocessor communication is needed when necessary and it runs under the MPI (Message passing interface) that allows parallel execution on heterogeneous SUN cluster of workstation platform. The program code is written in C language and executed under UNIX operating system (Solaris version).

Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memorysystems.However, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

An efficient approach for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations

An efficient approach is proposed for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations.The concentrated plastic hinges,described by the Bouc-Wen model,are assumed to occur at the two ends of a linear-elastic beam element.The auxiliary differential equations governing the plastic rotational displacements and their corresponding hysteretic displacements are replaced with linearized differential equations.Then,the two sets of equations of motion for the original nonlinear system can be reduced to an expanded-order equivalent linearized equation of motion for equivalent linear systems.To solve the equation of motion for equivalent linear systems,the nonstationary random vibration analysis is carried out based on the explicit time-domain method with high efficiency.Finally,the proposed treatment method for initial values of equivalent parameters is investigated in conjunction with parallel computing technology,which provides a new way of obtaining the equivalent linear systems at different time instants.Based on the explicit time-domain method,the key responses of interest of the converged equivalent linear system can be calculated through dimension reduction analysis with high efficiency.Numerical examples indicate that the proposed approach has high computational efficiency,and shows good applicability to weak nonlinear and medium-intensity nonlinear systems.

Three-dimensional finite element simulation and reconstruction of jointed rock models using CT scanning and photogrammetry

The geometry of joints has a significant influence on the mechanical properties of rocks.To simplify the curved joint shapes in rocks,the joint shape is usually treated as straight lines or planes in most laboratory experiments and numerical simulations.In this study,the computerized tomography (CT) scanning and photogrammetry were employed to obtain the internal and surface joint structures of a limestone sample,respectively.To describe the joint geometry,the edge detection algorithms and a three-dimensional (3D) matrix mapping method were applied to reconstruct CT-based and photogrammetry-based jointed rock models.For comparison tests,the numerical uniaxial compression tests were conducted on an intact rock sample and a sample with a joint simplified to a plane using the parallel computing method.The results indicate that the mechanical characteristics and failure process of jointed rocks are significantly affected by the geometry of joints.The presence of joints reduces the uniaxial compressive strength (UCS),elastic modulus,and released acoustic emission (AE) energy of rocks by 37%–67%,21%–24%,and 52%–90%,respectively.Compared to the simplified joint sample,the proposed photogrammetry-based numerical model makes the most of the limited geometry information of joints.The UCS,accumulative released AE energy,and elastic modulus of the photogrammetry-based sample were found to be very close to those of the CT-based sample.The UCS value of the simplified joint sample (i.e.38.5 MPa) is much lower than that of the CT-based sample (i.e.72.3 MPa).Additionally,the accumulative released AE energy observed in the simplified joint sample is 3.899 times lower than that observed in the CT-based sample.CT scanning provides a reliable means to visualize the joints in rocks,which can be used to verify the reliability of photogrammetry techniques.The application of the photogrammetry-based sample enables detailed analysis for estimating the mechanical properties of jointed rocks.