Robust and portable capacity computing method for many finite element analyses of a high-fidelity crustal structure model aimed for coseismic slip estimation

Agata, Ryoichiro; Ichimura, Tsuyoshi; Hirahara, Kazuro; Hyodo, Mamoru; Hori, Takane; Hori, Muneo

doi:10.1016/j.cageo.2016.05.015

Cited by 8 publications

(6 citation statements)

References 29 publications

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“…Figure 10 shows the estimated slip distribution obtained by solving Eq. (5) using the computed Green's functions and observed data, a result consistent with previous studies [18]. Fig.…”

Section: Performance Measurementssupporting

confidence: 92%

See 1 more Smart Citation

Implicit Low-Order Unstructured Finite-Element Multiple Simulation Enhanced by Dense Computation Using OpenACC

Yamaguchi

Fujita

Ichimura

et al. 2018

Accelerator Programming Using Directives

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In this paper, we develop a low-order three-dimensional finite-element solver for fast multiple-case crust deformation computation on GPU-based systems. Based on a highperformance solver designed for massively parallel CPU-based systems, we modify the algorithm to reduce random data access, and then insert OpenACC directives. By developing algorithm appropriate for each computer architecture, we enable to exhibit higher performance. The developed solver on ten Reedbush-H nodes (20 P100 GPUs) attained speedup of 14.2 times from the original solver on 20 K computer nodes. On the newest Volta generation V100 GPUs, the solver attained a further 2.52 times speedup with respect to P100 GPUs. As a demonstrative example, we computed 368 cases of crustal deformation analyses of northeast Japan with 400 million degrees of freedom. The total procedure of algorithm modification and porting implementation took only two weeks; we can see that high performance improvement was achieved with low development cost. With the developed solver, we can expect improvement in reliability of crust-deformation analyses by many-case analyses on a wide range of GPU-based systems.

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“…Figure 10 shows the estimated slip distribution obtained by solving Eq. (5) using the computed Green's functions and observed data, a result consistent with previous studies [18]. Fig.…”

Section: Performance Measurementssupporting

confidence: 92%

“…First, we describe the method used to estimate the coseismic fault slip distribution following a previous study [18]. The assumed fault plane is divided into n small unit faults, and the fault slip is expanded using these unit faults as bases:…”

Section: Performance Measurementsmentioning

confidence: 99%

Implicit Low-Order Unstructured Finite-Element Multiple Simulation Enhanced by Dense Computation Using OpenACC

Yamaguchi

Fujita

Ichimura

et al. 2018

Accelerator Programming Using Directives

Self Cite

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show abstract

“…We used the x, y and z components of displacement from GEONET, the x and y components from GPS-A, and the z component from S-NET. These settings for Green's functions and observational data were the same as those in the inversion analysis by Agata et al (2016).…”

Section: Multiple Computation Examplementioning

confidence: 99%

Fast crustal deformation computing method for multiple computations accelerated by a graphics processing unit cluster

Yamaguchi¹,

Ichimura²,

Yagi

et al. 2017

Geophysical Journal International

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As high-resolution observational data become more common, the demand for numerical simulations of crustal deformation using 3-D high-fidelity modelling is increasing. To increase the efficiency of performing numerical simulations with high computation costs, we developed a fast solver using heterogeneous computing, with graphics processing units (GPUs) and central processing units, and then used the solver in crustal deformation computations. The solver was based on an iterative solver and was devised so that a large proportion of the computation was calculated more quickly using GPUs. To confirm the utility of the proposed solver, we demonstrated a numerical simulation of the coseismic slip distribution estimation, which requires 360 000 crustal deformation computations with 82 196 106 degrees of freedom.

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“…Figure 3(c) shows the central points of the unit small faults. Although the proposed method enables the computation of single G ij in a short time, computation of all of G ij is accelerated by performing input/output operations e±ciently with the algorithm of Agata et al [2016]. With the presented improvements, we computed all of the G ij in 23.7 h using 16 computer nodes of a PC cluster (each node had 12 computer cores and 48 GB computer memory; 16 nodes of IntelR Xeon X5680 [6-core 3.33 GHz/12 MB/QPI-6.4 GT/s]; Â 2 and 8 GB [DDR3-1333 Registered ECC] Â 6).…”

Section: Numerical Experimentsmentioning

confidence: 99%

Tsunami Analysis Method with High-Fidelity Crustal Structure and Geometry Model

Ichimura

Agata

Hori

et al. 2017

J. Earthquake and Tsunami

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Higher¯delity sea°oor topography and crustal structure models have become available with accumulation of observation data. Previous studies have shown that the consideration of such high-¯delity models produces signi¯cant e®ects, in some cases, on crustal deformation results that are used as inputs for tsunami analysis. However, it is di±cult to apply high-¯delity model of crustal deformation computations to tsunami computations because of large computational costs. In this paper, we propose a new crustal deformation computation method for estimating inputs for tsunami computations, which is based on a¯nite element analysis method with remarkable reduction of computation costs by e±cient use of the arithmetic space and the solution space. This¯nite element analysis method enables us to conduct 10 2À3 -times crustal deformation computations using high-¯delity models with a degree of freedom on the order of 10 8 for the 2011 Tohoku earthquake example. Tsunami computations with typical settings are conducted as an application example to present the advantages and characteristics of the proposed method. Comparisons between results of the proposed and the conventional method

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Robust and portable capacity computing method for many finite element analyses of a high-fidelity crustal structure model aimed for coseismic slip estimation

Cited by 8 publications

References 29 publications

Implicit Low-Order Unstructured Finite-Element Multiple Simulation Enhanced by Dense Computation Using OpenACC

Implicit Low-Order Unstructured Finite-Element Multiple Simulation Enhanced by Dense Computation Using OpenACC

Fast crustal deformation computing method for multiple computations accelerated by a graphics processing unit cluster

Tsunami Analysis Method with High-Fidelity Crustal Structure and Geometry Model

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