@inproceedings{francois2014volume,
title = {VOLUME-OF-FLUID INTERFACE RECONSTRUCTION ALGORITHMS ON NEXT-GENERATION COMPUTER ARCHITECTURES},
author = {Marianne M Francois and Li-Ta Lo and Christopher Sewell},
url = {http://datascience.dsscale.org/wp-content/uploads/sites/3/2016/06/Volume-Of-FluidInterfaceReconstructionAlgorighmsOnNext-GenerationComputerArchitectures.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the ASME},
abstract = {With the increasing heterogeneity and on-node parallelism of high-performance computing hardware, a major challenge to computational physicists is to work in close collaboration with computer scientists to develop portable and efficient algorithms and software. The objective of our work is to implement a portable code to perform interface reconstruction using NVIDIA’s Thrust library. Interface reconstruction is a technique commonly used in volume tracking methods for simulations of interfacial flows. For that, we have designed a two-dimensional mesh data structure that is easily mapped to the 1D vectors used by Thrust and at the same time is simple to work with using familiar data structures terminology (such as cell, vertices and edges). With this new data structure in place, we have implemented a recursive volume-of-fluid initialization algorithm and a standard piecewise interface reconstruction algorithm. Our interface reconstruction algorithm makes use of a table look-up to easily identify all intersection cases, as this design is efficient on parallel architectures such as GPUs. Finally, we report performance results which show that a single implementation of these algorithms can be compiled to multiple backends (specifically, multi-core CPUs, NVIDIA GPUs, and Intel Xeon Phi coprocessors), making efficient use of the available parallelism on each.},
note = {LA-UR-14-20777},
keywords = {COMPUTER ARCHITECTURES, INTERFACE RECONSTRUCTION, PISTON},
pubstate = {published},
tppubtype = {inproceedings}
}

With the increasing heterogeneity and on-node parallelism of high-performance computing hardware, a major challenge to computational physicists is to work in close collaboration with computer scientists to develop portable and efficient algorithms and software. The objective of our work is to implement a portable code to perform interface reconstruction using NVIDIA’s Thrust library. Interface reconstruction is a technique commonly used in volume tracking methods for simulations of interfacial flows. For that, we have designed a two-dimensional mesh data structure that is easily mapped to the 1D vectors used by Thrust and at the same time is simple to work with using familiar data structures terminology (such as cell, vertices and edges). With this new data structure in place, we have implemented a recursive volume-of-fluid initialization algorithm and a standard piecewise interface reconstruction algorithm. Our interface reconstruction algorithm makes use of a table look-up to easily identify all intersection cases, as this design is efficient on parallel architectures such as GPUs. Finally, we report performance results which show that a single implementation of these algorithms can be compiled to multiple backends (specifically, multi-core CPUs, NVIDIA GPUs, and Intel Xeon Phi coprocessors), making efficient use of the available parallelism on each.