Mixed-precision implementation of block <i>ϵ</i>-circulant preconditioner on modern CPU-GPU environments

Parallel-in-time methods for time-dependent problems have risen to prominence over the past decade as massively parallel computers push core counts into the millions. Among them, the block ϵ-circulant (BEC) preconditioned solver achieves outstanding convergence, yet the preconditioner itself dominates the solver runtime. We propose a mixed-precision strategy that uses single precision for BEC preconditioning and double precision elsewhere, thereby reducing the solver runtime especially on CPU-GPU systems. On an NVIDIA GH200 cluster, the mixed-precision BEC-GMRES solver achieves a 1.42× speedup for two-dimensional advection-diffusion problems without significant loss of accuracy.

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Publication Details

Journal
JSIAM Letters
Published
2025-01-01
DOI
https://doi.org/10.14495/jsiaml.17.85
Citations
1
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
1.50
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article

Mixed-precision implementation of block ϵ-circulant preconditioner on modern CPU-GPU environments

Matthias Bolten, Ryo Yoda
1 citations
JSIAM Letters
Matrix Theory and Algorithms
1.50
article

Mixed-precision implementation of block ϵ-circulant preconditioner on modern CPU-GPU environments

Matthias Bolten, Ryo Yoda
article en
1 citations

Abstract

Parallel-in-time methods for time-dependent problems have risen to prominence over the past decade as massively parallel computers push core counts into the millions. Among them, the block ϵ-circulant (BEC) preconditioned solver achieves outstanding convergence, yet the preconditioner itself dominates the solver runtime. We propose a mixed-precision strategy that uses single precision for BEC preconditioning and double precision elsewhere, thereby reducing the solver runtime especially on CPU-GPU systems. On an NVIDIA GH200 cluster, the mixed-precision BEC-GMRES solver achieves a 1.42× speedup for two-dimensional advection-diffusion problems without significant loss of accuracy.

JSIAM LettersVol. 17(0)
University of Wuppertal (DE)
Openalex Percentile: Top 12%
Matrix Theory and Algorithms
1.50
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