TY - GEN
T1 - Viscoelastic Crustal Deformation Computation Method with Reduced Random Memory Accesses for GPU-Based Computers
AU - Yamaguchi, Takuma
AU - Fujita, Kohei
AU - Ichimura, Tsuyoshi
AU - Glerum, Anne
AU - van Dinther, Ylona
AU - Hori, Takane
AU - Schenk, Olaf
AU - Hori, Muneo
AU - Wijerathne, Lalith
PY - 2018/6/12
Y1 - 2018/6/12
N2 - The computation of crustal deformation following a given fault slip is important for understanding earthquake generation processes and reduction of damage. In crustal deformation analysis, reflecting the complex geometry and material heterogeneity of the crust is important, and use of large-scale unstructured finite-element method is suitable. However, since the computation area is large, its computation cost has been a bottleneck. In this study, we develop a fast unstructured finite-element solver for GPU-based large-scale computers. By computing several times steps together, we reduce random access, together with the use of predictors suitable for viscoelastic analysis to reduce the total computational cost. The developed solver enabled 2.79 times speedup from the conventional solver. We show an application example of the developed method through a viscoelastic deformation analysis of the Eastern Mediterranean crust and mantle following a hypothetical M ?9 earthquake in Greece by using a 2,403,562,056 degree-of-freedom finite-element model.
AB - The computation of crustal deformation following a given fault slip is important for understanding earthquake generation processes and reduction of damage. In crustal deformation analysis, reflecting the complex geometry and material heterogeneity of the crust is important, and use of large-scale unstructured finite-element method is suitable. However, since the computation area is large, its computation cost has been a bottleneck. In this study, we develop a fast unstructured finite-element solver for GPU-based large-scale computers. By computing several times steps together, we reduce random access, together with the use of predictors suitable for viscoelastic analysis to reduce the total computational cost. The developed solver enabled 2.79 times speedup from the conventional solver. We show an application example of the developed method through a viscoelastic deformation analysis of the Eastern Mediterranean crust and mantle following a hypothetical M ?9 earthquake in Greece by using a 2,403,562,056 degree-of-freedom finite-element model.
KW - Conjugate gradient method
KW - CUDA
KW - Finite element analysis
UR - http://www.scopus.com/inward/record.url?scp=85049099738&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-93701-4_3
DO - 10.1007/978-3-319-93701-4_3
M3 - Conference contribution
AN - SCOPUS:85049099738
SN - 9783319937007
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 31
EP - 43
BT - Computational Science – ICCS 2018 - 18th International Conference, Proceedings
PB - Springer
T2 - 18th International Conference on Computational Science, ICCS 2018
Y2 - 11 June 2018 through 13 June 2018
ER -