@inproceedings{0439ec5133ff4673bdcf7bbb3d99d3ec,
title = "Brief Announcement: Faster Stencil Computations using Gaussian Approximations",
abstract = "Stencil computations are widely used to simulate the change of state of physical systems. The current best algorithm for performing aperiodic linear stencil computations on a d (= 1)-dimensional grid of size N for T timesteps does ?(TN1-1/d + N Log N) work. We introduce novel techniques based on random walks and Gaussian approximations for an asymptotic improvement of this work bound for a class of linear stencils. We also improve the span (i.e., parallel running time on an unbounded number of processors) asymptotically from the current state of the art.",
keywords = "fast gauss transform, gaussian approximation, linear stencil",
author = "Zafar Ahmad and Rezaul Chowdhury and Rathish Das and Pramod Ganapathi and Aaron Gregory and Yimin Zhu",
note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 34th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2022 ; Conference date: 11-07-2022 Through 14-07-2022",
year = "2022",
month = jul,
day = "11",
doi = "10.1145/3490148.3538558",
language = "English",
series = "Annual ACM Symposium on Parallelism in Algorithms and Architectures",
publisher = "Association for Computing Machinery",
pages = "291--293",
booktitle = "SPAA 2022 - Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures",
}