Porting hypre to heterogeneous computer architectures: Strategies and experiences

We report that linear systems are occurring in many applications, and solving them can take a large amount of the total simulation time. The high performance library hypre provides a variety of interfaces and linear solvers, including various multigrid methods, that have achieved good scalability on...

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Bibliographic Details
Published in:Parallel computing 2021-09, Vol.108 (N/A)
Main Authors: Falgout, Robert D., Li, Ruipeng, Sjögreen, Björn, Wang, Lu, Yang, Ulrike Meier
Format: Article
Language:English
Subjects:
GPU computing
HPC
iterative methods
MATHEMATICS AND COMPUTING
multigrid methods
preconditioning techniques
Online Access:Get full text
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Summary:We report that linear systems are occurring in many applications, and solving them can take a large amount of the total simulation time. The high performance library hypre provides a variety of interfaces and linear solvers, including various multigrid methods, that have achieved good scalability on a variety of homogeneous parallel computer architectures. Heterogeneous architectures with nodes that have both CPUs and accelerators provide new challenges, since they require more fine-grained parallelism and reduced data movement between different memories on a single node as well as across nodes. We will discuss our experiences and strategies to port hypre to heterogeneous computers with accelerators, including the design of a new memory model, the use of abstractions, the BoxLoop macros in the structured and semi-structured interfaces, and the restructuring of algebraic multigrid (AMG) into modular components. We present numerical experiments comparing CPU and GPU performance for several test problems.
ISSN:0167-8191
1872-7336