A GPU parallel Bernstein algorithm for polynomial global optimization
| Autor: | P. S. Dhabe, P. S. V. Nataraj |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Polynomial
021103 operations research Computer science Strategy and Management 0211 other engineering and technologies Graphics processing unit Parallel algorithm 010103 numerical & computational mathematics 02 engineering and technology Interval (mathematics) 01 natural sciences Set (abstract data type) Test suite 0101 mathematics Safety Risk Reliability and Quality Global optimization Algorithm Matrix method |
| Zdroj: | International Journal of System Assurance Engineering and Management. 11:21-44 |
| ISSN: | 0976-4348 0975-6809 |
| DOI: | 10.1007/s13198-019-00922-6 |
| Popis: | We come up with a graphics processing unit (GPU) parallel Bernstein algorithm (BA) aimed at global optimization of multi-variate real polynomials (Garloff in Interval Comput 2:164–168, 1993). We first propose parallel algorithms for (a) computing the multi-index set associated with the Bernstein coefficients (BCs), (b) computing the initial set of BCs using the Matrix method (Ray and Nataraj in Reliab Comput 17(1):40–71, 2012), (c) finding the minimum BC from a given set of BCs, and (d) finding the BCs of the child patches from the parent patch. We then incorporate the above components into the proposed parallel Bernstein algorithm. All the parallel algorithms are programmed for GPU accelerating devices through compute unified device architecture. We compared performance of serial and GPU parallel BA using a test suite of 8 multivariate examples. For the test examples, the proposed parallel algorithm is found 30 times faster as compared to serial one, and needs 96% less time. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink