<span class="var-sub_title">A Parallel-Efficient GPU Package for Multiphase Flow in Realistic Nano-Pore Networks</span> SC18 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

A Parallel-Efficient GPU Package for Multiphase Flow in Realistic Nano-Pore Networks

Authors: Yidong Xia (Idaho National Laboratory), Ansel Blumers (Brown University, Idaho National Laboratory), Zhen Li (Brown University), Lixiang Luo (IBM), Jan Goral (University of Utah), Matthew Andrew (Carl Zeiss X-ray Microscopy Inc), Joshua Kane (Idaho National Laboratory), Yu-Hang Tang (Lawrence Berkeley National Laboratory)

Abstract: Simulations of fluid flow in oil/gas shale rocks are challenging in part due to the heterogeneous pore sizes ranging from a few nanometers to a few micrometers. Additionally, the complex fluid-solid interaction occurring physically and chemically must be captured with high resolution. To address these challenges while minimizing computational cost, we present a GPU code that has implemented a many-body dissipative particle dynamics (mDPD) model for multiphase flow in shale. Realistic nano- to micro-pore channels in shale are constructed from 3D high-resolution stack images. In our benchmark tests, the code delivers nearly perfect weak and strong scalings on up to 512 K20X GPUs on Oak Ridge National Laboratory (ORNL) Titan supercomputer. Moreover, single-GPU bench-marks on the DGX-1 (V100/no NVLink), ORNL’s SummitDev (P100/NVLink 1.0) and Summit (V100/NVLink 2.0) suggest that the latest Host-to-Device NVLink can significantly boost overall performance, in addition to the Device-to-Device NVLink.

Best Poster Finalist (BP): no

Poster: pdf
Poster summary: PDF
Reproducibility Description Appendix: PDF

Back to Poster Archive Listing