Copyrights to these papers may be held by the publishers. The download files are preprints. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Anuva Kulkarni, Daniele G. Spampinato and Franz Franchetti (Supercomputing, 2019)
Design and Specification of Large-scale Simulations for GPUs using FFTX
Published paper (link to publisher)
Bibtex

Large-scale scientific simulations can be ported to heterogeneous environments with GPUs using domain decomposition. However, Fast Fourier Transform (FFT) based simulations require all-to-all communication and large memory, which is beyond the capacity of on-chip GPU memory. To overcome this, domain decomposition solutions are combined with adaptive sampling or pruning around the domain to reduce storage. Expression of such operations is a challenge in existing FFT libraries like FFTW, and thus it is difficult to get a high performance implementation of such methods. We demonstrate algorithm specification for one such simulation (Hooke's law) using FFTX, an emerging API with a SPIRAL-based code generation back-end, and suggest future extensions useful for GPU-based scientific computing.

Keywords:
Simulation, Design, GPUs, Large Scale, FFTX