Abstract
Peridynamic (PD) codes, which are written by using any programming language, e.g., C, C++, FORTRAN, or Java, can be run in any available computing facility. This can be a desktop/laptop computer or a high performance computing (HPC) facility. Nowadays, desktops/laptops include many central processing units (CPUs) and relatedly many cores in their architectures. Moreover, graphical processing units (GPUs) of computers have been improved above and beyond the expectations. Either one of them or both of them can be benefited in order to solve large and complicated problems in personal desktops/laptops. This chapter presents how it is possible to improve PD codes and make them efficient for large-scale problems with the help of parallel programming procedures. Moreover, how simple modifications with very basic knowledge of parallel programming skills can lead to significant increase in our calculation speeds is demonstrated. Specifically, CPU- and GPU-based approaches are explained for parallelizing PD codes.
| Original language | English |
|---|---|
| Title of host publication | Peridynamic Modeling, Numerical Techniques, and Applications |
| Publisher | Elsevier |
| Pages | 403-417 |
| Number of pages | 15 |
| ISBN (Electronic) | 9780128200698 |
| DOIs | |
| State | Published - Jan 1 2021 |
Keywords
- Central processing units
- Graphical processing units
- High performance computing
- Parallel programming
- Peridynamics
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