A fine-grained parallelization of the immersed boundary method

Author:

Kassen Andrew1ORCID,Shankar Varun2,Fogelson Aaron L3

Affiliation:

1. Intel Corporation, Santa Clara, CA, USA

2. School of Computing, University of Utah, Salt Lake City, UT, USA

3. Departments of Mathematics and Biomedical Engineering, University of Utah, Salt Lake City, UT, USA

Abstract

We present new algorithms for the parallelization of Eulerian–Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of these parallel primitives allows us to implement our algorithms on both graphics processing units (GPUs) and on other shared-memory architectures. We present strong and weak scaling tests on problems involving scattered points and elastic structures. Our tests show that our algorithms exhibit near-ideal scaling on both multicore CPUs and GPUs.

Funder

Division of Mathematical Sciences

Division of Computing and Communication Foundations

Publisher

SAGE Publications

Subject

Hardware and Architecture,Theoretical Computer Science,Software

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