Abstract
In a recent publication (Eghtesad et al., 2018), we have reported a message passing interface (MPI)-based domain decomposition parallel implementation of an elasto-viscoplastic fast Fourier transform-based (EVPFFT) micromechanical solver to facilitate computationally efficient crystal plasticity modeling of polycrystalline materials. In this paper, we present major extensions to the previously reported implementation to take advantage of graphics processing units (GPUs), which can perform floating point arithmetic operations much faster than traditional central processing units (CPUs). In particular, the applications are developed to utilize a single GPU and multiple GPUs from one computer as well as a large number of GPUs across nodes of a supercomputer. To this end, the implementation combines the OpenACC programming model for GPU acceleration with MPI for distributed computing. Moreover, the FFT calculations are performed using the efficient Compute Unified Device Architecture (CUDA) FFT library, called CUFFT. Finally, to maintain performance portability, OpenACC-CUDA interoperability for data transfers between CPU and GPUs is used. The overall implementations are termed ACC-EVPCUFFT for single GPU and MPI-ACC-EVPCUFFT for multiple GPUs. To facilitate performance evaluation studies of the developed computational framework, deformation of a single phase copper is simulated, while to further demonstrate utility of the implementation for resolving fine microstructures, deformation of a dual-phase steel DP590 is simulated. The implementations and results are presented and discussed in this paper.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.