In EDS ansehen

A Subdomain-Based GPU Parallel Scheme for Accelerating Perdynamics Modeling with Reduced Graphics Memory.

Gespeichert in:
Bibliographische Detailangaben
Titel: A Subdomain-Based GPU Parallel Scheme for Accelerating Perdynamics Modeling with Reduced Graphics Memory.
Autoren: Yang, Zuokun, Li, Jun, Lai, Xin, Liu, Lisheng
Quelle: Computer Modeling in Engineering & Sciences (CMES); 2026, Vol. 146 Issue 1, p1-30, 30p
Schlagwörter: GRAPHICS processing units, PARALLEL algorithms, DATA structures, COMPUTATIONAL mechanics, DATA management, COMPUTER performance
Abstract: Peridynamics (PD) demonstrates unique advantages in addressing fracture problems, however, its nonlocality and meshfree discretization result in high computational and storage costs. Moreover, in its engineering applications, the computational scale of classical GPU parallel schemes is often limited by the finite graphics memory of GPU devices. In the present study, we develop an efficient particle information management strategy based on the cell-linked list method and on this basis propose a subdomain-based GPU parallel scheme, which exhibits outstanding acceleration performance in specific compute kernels while significantly reducing graphics memory usage. Compared to the classical parallel scheme, the cell-linked list method facilitates efficient management of particle information within subdomains, enabling the proposed parallel scheme to effectively reduce graphics memory usage by optimizing the size and number of subdomains while significantly improving the speed of neighbor search. As demonstrated in PD examples, the proposed parallel scheme enhances the neighbor search efficiency dramatically and achieves a significant speedup relative to serial programs. For instance, without considering the time of data transmission, the proposed scheme achieves a remarkable speedup of nearly 1076.8× in one test case, due to its excellent computational efficiency in the neighbor search. Additionally, for 2D and 3D PD models with tens of millions of particles, the graphics memory usage can be reduced up to 83.6% and 85.9%, respectively. Therefore, this subdomain-based GPU parallel scheme effectively avoids graphics memory shortages while significantly improving the computational efficiency, providing new insights into studying more complex large-scale problems. [ABSTRACT FROM AUTHOR]
Copyright of Computer Modeling in Engineering & Sciences (CMES) is the property of Tech Science Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Datenbank: Complementary Index
Beschreibung
Abstract:Peridynamics (PD) demonstrates unique advantages in addressing fracture problems, however, its nonlocality and meshfree discretization result in high computational and storage costs. Moreover, in its engineering applications, the computational scale of classical GPU parallel schemes is often limited by the finite graphics memory of GPU devices. In the present study, we develop an efficient particle information management strategy based on the cell-linked list method and on this basis propose a subdomain-based GPU parallel scheme, which exhibits outstanding acceleration performance in specific compute kernels while significantly reducing graphics memory usage. Compared to the classical parallel scheme, the cell-linked list method facilitates efficient management of particle information within subdomains, enabling the proposed parallel scheme to effectively reduce graphics memory usage by optimizing the size and number of subdomains while significantly improving the speed of neighbor search. As demonstrated in PD examples, the proposed parallel scheme enhances the neighbor search efficiency dramatically and achieves a significant speedup relative to serial programs. For instance, without considering the time of data transmission, the proposed scheme achieves a remarkable speedup of nearly 1076.8× in one test case, due to its excellent computational efficiency in the neighbor search. Additionally, for 2D and 3D PD models with tens of millions of particles, the graphics memory usage can be reduced up to 83.6% and 85.9%, respectively. Therefore, this subdomain-based GPU parallel scheme effectively avoids graphics memory shortages while significantly improving the computational efficiency, providing new insights into studying more complex large-scale problems. [ABSTRACT FROM AUTHOR]
ISSN:15261492
DOI:10.32604/cmes.2026.075980