Computational Physics GroupKarel Matous |
||||||||||
|
Computational Homogenization at Extreme Scales
Department of Aerospace and Mechanical Engineering University of Notre Dame Notre Dame, IN, 46556, USA. Abstract Multi-scale
simulations at extreme scales in terms of both physical
length scales and computational resources are presented.
In this letter, we introduce a hierarchically parallel
computational homogenization solver that employs
hundreds of thousands of computing cores and resolves O(105)
in material length scales (from O(cm) to O(100
nm)). Simulations of this kind are essential in
understanding the multi-scale essence of many natural
and synthetically made materials. Thus, we present a
simulation consisting of 53.8 Billion finite elements
with 28.1 Billion nonlinear equations that is solved on
393,216 computing cores (786,432 threads). The excellent
parallel performance of the computational homogenization
solver is demonstrated by a strong scaling test from
4,096 to 262,114 cores. A fully coupled multi-scale
damage simulation shows a complex crack profile at the
micro-scale and the macroscopic crack tunneling
phenomenon. Such large and predictive simulations are an
important step towards Virtual Materials Testing
and can aid in development of new material formulations
with extreme properties. Furthermore, the high
computational efficiency of our computational
homogenization solver holds great promise for utilizing
the next generation of exascale parallel computing
platforms that are expected to accelerate computations
through orders of magnitude increase in parallelism
rather than speed of each processor.
ConclusionsWe have presented extreme scale computations, in terms of both physical scales and computing resources, containing ∼54B finite elements, over 28B nonlinear DOFs and executed on ∼400 thousand computing cores. Such large and detailed simulations are necessary for better understanding of complex (i.e., rate-dependent) multi-scale material behavior under nontrivial loading conditions. Moreover, with co-designed experiments and properly validated constitutive models, such large predictive simulations can be the basis of “Virtual Materials Testing” standards, and aid in development of new material formulations with extreme properties. These large simulations were enabled by a hierarchically parallel CH solver with excellent computational scaling behavior. The high scalability of the CH method makes it a promising approach for efficiently utilizing the future massively parallel exascale platforms. Acknowledgments
|