GPU-powered, interactive flow simulation on a peer-to-peer group of mobile devices

摘要

This article develops novel application software which implements interactive, GPU-powered flow simulation on a group of wirelessly-connected mobile devices. Interactive simulation is an emerging field in engineering with use cases appearing in design, analysis and communication. Herein, we present a new Android-based, interactive flow solver capable of running on a wider range of multiple, wirelessly-connected mobile GPUs. The software consists of a 2D Lattice-Boltzmann Method flow physics solver, implemented using OpenGL ES 3.2, as well as a communication library which uses Wi-Fi Direct to communicate between connected devices. We compare the performance of the OpenGL-based solver against existing implementations in CUDA and demonstrate similar computational throughput. We also test a variety of communication strategies based on configurations of GPU memory mapping and communication frequency. Results confirm that passing large amounts of data infrequently offers the best overall efficiency. However, due to the extended time required to pass larger amounts of data to adjacent devices, this configuration can introduce an undesirable stuttering in an interactive application. Finally, comparisons between two and three device networks to the serial case show that, despite the inevitable cost of communication, it is possible to maintain an interactive frame rate across multiple devices; the extension of calculations across multiple devices in this way, allows the tackling of problems which are larger and of higher-resolution that previous.