Automated MPI-X code generation for scalable finite-difference solvers
OA Location
Author(s)
Type
Conference Paper
Abstract
Partial differential equations (PDEs) are crucial in modeling diverse phenomena across scientific disciplines, including seismic and medical imaging, computational fluid dynamics, image processing, and neural networks. Solving these PDEs at scale is an intricate and time-intensive process that demands careful tuning. This paper introduces automated codegeneration techniques specifically tailored for distributed memory parallelism (DMP) to execute explicit finite-difference (FD) stencils at scale, a fundamental challenge in numerous scientific applications. These techniques are implemented and integrated into the Devito DSL and compiler framework, a well-established solution for automating the generation of FD solvers based on a high-level symbolic math input. Users benefit from modeling simulations for real-world applications at a high-level symbolic abstraction and effortlessly harnessing HPC-ready distributedmemory parallelism without altering their source code. This results in drastic reductions both in execution time and developer effort. A comprehensive performance evaluation of Devito's DMP via MPI demonstrates highly competitive strong and weak scaling on CPU and GPU clusters, proving its effectiveness and capability to meet the demands of large-scale scientific simulations.
Date Issued
2025-07-23
Date Acceptance
2025-06-01
Citation
2025 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2025, pp.689-701
ISBN
979-8-3315-3238-3
ISSN
1530-2075
Publisher
IEEE Computer Society
Start Page
689
End Page
701
Journal / Book Title
2025 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
Copyright Statement
Copyright © 2025, IEEE.
Source
2025 International Parallel and Distributed Processing Symposium-IPDPS-Annual
Subjects
compilation
Computer Science
Computer Science, Theory & Methods
CPUs
distributed-memory parallelism
DSLs
finite-difference method
FRAMEWORK
GPUs
high-performance computing
MPI
PERFORMANCE
REVERSE-TIME MIGRATION
Science & Technology
SIMULATION
stencil computation
symbolic computation
Technology
WAVE PROPAGATION
Publication Status
Published
Start Date
2025-06-03
Finish Date
2025-06-07
Coverage Spatial
Milan, Milan