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Autori principali: Long, Shiting, Ramirez-Hidalgo, Gustavo, Nassyr, Stepan, Jimenez-Merchan, Jose, Frommer, Andreas, Pleiter, Dirk
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2601.05816
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author Long, Shiting
Ramirez-Hidalgo, Gustavo
Nassyr, Stepan
Jimenez-Merchan, Jose
Frommer, Andreas
Pleiter, Dirk
author_facet Long, Shiting
Ramirez-Hidalgo, Gustavo
Nassyr, Stepan
Jimenez-Merchan, Jose
Frommer, Andreas
Pleiter, Dirk
contents Managing the high computational cost of iterative solvers for sparse linear systems is a known challenge in scientific computing. Moreover, scientific applications often face memory bandwidth constraints, making it critical to optimize data locality and enhance the efficiency of data transport. We extend the lattice QCD solver DD-$α$AMG to incorporate multiple right-hand sides (rhs) for both the Wilson-Dirac operator evaluation and the GMRES solver, with and without odd-even preconditioning. To optimize auto-vectorization, we introduce a flexible interface that supports various data layouts and implement a new data layout for better SIMD utilization. We evaluate our optimizations on both x86 and Arm clusters, demonstrating performance portability with similar speedups. A key contribution of this work is the performance analysis of our optimizations, which reveals the complexity introduced by architectural constraints and compiler behavior. Additionally, we explore different implementations leveraging a new matrix instruction set for Arm called SME and provide an early assessment of its potential benefits.
format Preprint
id arxiv_https___arxiv_org_abs_2601_05816
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Performance-Portable Optimization and Analysis of Multiple Right-Hand Sides in a Lattice QCD Solver
Long, Shiting
Ramirez-Hidalgo, Gustavo
Nassyr, Stepan
Jimenez-Merchan, Jose
Frommer, Andreas
Pleiter, Dirk
Distributed, Parallel, and Cluster Computing
High Energy Physics - Lattice
Managing the high computational cost of iterative solvers for sparse linear systems is a known challenge in scientific computing. Moreover, scientific applications often face memory bandwidth constraints, making it critical to optimize data locality and enhance the efficiency of data transport. We extend the lattice QCD solver DD-$α$AMG to incorporate multiple right-hand sides (rhs) for both the Wilson-Dirac operator evaluation and the GMRES solver, with and without odd-even preconditioning. To optimize auto-vectorization, we introduce a flexible interface that supports various data layouts and implement a new data layout for better SIMD utilization. We evaluate our optimizations on both x86 and Arm clusters, demonstrating performance portability with similar speedups. A key contribution of this work is the performance analysis of our optimizations, which reveals the complexity introduced by architectural constraints and compiler behavior. Additionally, we explore different implementations leveraging a new matrix instruction set for Arm called SME and provide an early assessment of its potential benefits.
title Performance-Portable Optimization and Analysis of Multiple Right-Hand Sides in a Lattice QCD Solver
topic Distributed, Parallel, and Cluster Computing
High Energy Physics - Lattice
url https://arxiv.org/abs/2601.05816