Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Accelerated isogeometric topology optimization with multi-graphics processing unit and multi-core central processing unit using proportional-integral-derivative load balancing. |
| Συγγραφείς: |
Gao, Baichuan, Liu, Jianli, Fan, Hongshuo, Nie, Tao, Yu, Jingui, Yang, Jianzhong, Xia, Zhaohui |
| Πηγή: |
Engineering Optimization; May2026, Vol. 58 Issue 5, p1461-1487, 27p |
| Θεματικοί όροι: |
Load balancing (Computer networks), Mathematical optimization, Scalability, Multicore processors, Parallel programming, Computer memory management |
| Περίληψη: |
This article proposes an accelerated isogeometric topology optimization (ITO) method using multi-graphics processing unit (GPU) and multi-core central processing unit (CPU) parallel computing with a proportional-integral-derivative (PID)-based dynamic load-balancing strategy. To optimize device memory utilization, a parallel computing framework integrating a task set division method is developed, effectively handling large-scale ITO problems. The PID control strategy dynamically adjusts workload distribution in real time based on node performance, ensuring balanced task execution across computational resources. Several three-dimensional numerical examples validate the proposed method, demonstrating effective CPU-GPU task allocation, significant memory efficiency improvements and enhanced scalability. The results confirm that the strategy optimally balances computational loads, reduces single-GPU memory constraints and enables the efficient resolution of large-scale topology optimization problems. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Complementary Index |