GPU parallelization of an object-oriented nonlinear dynamic structural analysis platform

Yang, Yuan–Sen; Yang, Chung-Ming; Hsieh, Tung-Ju

doi:10.1016/j.simpat.2013.09.004

Cited by 14 publications

(3 citation statements)

References 14 publications

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“…By using the STP, the time consumed in the state determination of elements in two example structures is reduced by 50%–88%. Owing to inherent independency existing in element state determination process, some parallel computing techniques, for example, graphics processing unit (GPU) computing techniques, can be easily applied to accelerate such process. Fiber beam‐column elements have a different discretization strategy from that of multilayered shear wall elements.…”

Section: Introductionmentioning

confidence: 99%

New speedup algorithms for nonlinear dynamic time history analysis of supertall building structures under strong earthquakes

Shi

et al. 2017

Structural Design Tall Build

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Some speedup algorithms oriented to improving computational efficiency of nonlinear dynamic time history analysis of supertall buildings structures excited by strong earthquakes are proposed. In order to minimize Jacobian factorizations, the inexact Newton algorithm combined with the sparse Cholesky matrix factorization (INC) is suggested with an unbalance-independent relation for the determination of a forcing term in the INC. Further, some shared memory parallel computing techniques are incorporated into the state transformation procedures developed previously (parallel state transformation procedure) and the matrix factorization (parallelized factorization) for full utilization of the resources of an ordinary personal computer. All the algorithms are integrated in a finite element program specialized in time history analysis of aseismic supertall building structures, with some features from OpenSees. Computational efficiency, as well as accuracy, of the proposed speedup algorithms is demonstrated on one 12-story reinforced concrete frame (K1) and 4 frame-core-tube supertall buildings (S1-S4). The results from the demonstration indicate that, as the number of degrees of freedom increases, the proportion of time consumed in Jacobian factorization becomes relatively more dominant. The combination of the INC and the parallelized factorization can achieve better acceleration performance in this case. Factors associated with the forcing term of the INC have much influence on computational efficiency and should be selected based on building scale. Combination of all the algorithms in the biggest model(S4) yields an average of 28.72 of acceleration ratio even with peak ground acceleration equal to 3.2 g. In all cases considered, a desirable agreement in structural response is always reached between conventional time history analysis method and the method using the proposed speedup algorithms.

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Section: Introductionmentioning

confidence: 99%

New speedup algorithms for nonlinear dynamic time history analysis of supertall building structures under strong earthquakes

Shi

et al. 2017

Structural Design Tall Build

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“…The GPU itself is a many‐core processor where dozens of streaming processors with hundreds of cores support thousands of threads running concurrently on single chip as depicted in Figure . Because the GPU hardware can be classified as single‐instruction, multiple threads, therefore general purpose CPU–based applications with significant data in‐dependency are well suited for such devices.…”

Section: Introductionmentioning

confidence: 99%

An optimized magnetostatic field solver on GPU using open computing language

Khan

Montrucchio

Jan

et al. 2016

Concurrency and Computation

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Summary Recent graphic processing units (GPUs) have remarkable raw computing power, which can be used for very computationally challenging problems. Like in micromagnetic simulations, where the magnetostatic field computation to analyze the magnetic behavior at very small time and space scale demands a huge computation time. This paper presents a multidimensional FFT‐based parallel implementation of a magnetostatic field computation on GPUs. We have developed a specialized 3D FFT library for magnetostatic field calculation on GPUs. This made it possible to fully exploit the symmetries inherent in the field calculation and other optimizations specific to the GPUs architecture. We have compared our results with the widely used CPU‐based parallel OOMMF program and with an equivalent serial implementation on CPU. The results have shown a speedup of up to 95x and 8.7x for single and 66x and 4.6x for double precision floating point accuracy against equivalent serial implementation and OOMMF, respectively.

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“…The directions, patterns, and density of crack distributions reveal different failure modes, the degradation of stiffness and strength of structures, and many other kinds of significant information to researchers (e.g., Figs. 1a and 1b) for failure mode studies [1] and numerical model development [2][3]. Conventionally, cracks are observed by suspending a test to allow inspectors to approach the concrete surfaces and manually sketch lines on the cracks (Fig.…”

Section: Introductionmentioning

confidence: 99%

Thin crack observation in a reinforced concrete bridge pier test using image processing and analysis

Yang

Huang

2015

Advances in Engineering Software

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GPU parallelization of an object-oriented nonlinear dynamic structural analysis platform

Cited by 14 publications

References 14 publications

New speedup algorithms for nonlinear dynamic time history analysis of supertall building structures under strong earthquakes

New speedup algorithms for nonlinear dynamic time history analysis of supertall building structures under strong earthquakes

An optimized magnetostatic field solver on GPU using open computing language

Thin crack observation in a reinforced concrete bridge pier test using image processing and analysis

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