Sampathirao, Ajay Kumar and Sopasakis, Pantelis and Bemporad, Alberto and Patrinos, Panagiotis Distributed solution of stochastic optimal control problems on GPUs. In: 54th IEEE Conference on Decision and Control, 15-18 December, 2015, Osaka, Japan (2015)
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Abstract
Stochastic optimal control problems arise in many applications and are, in principle, large-scale involving up to millions of decision variables. Their applicability in control applications is often limited by the availability of algorithms that can solve them efficiently and within the sampling time of the controlled system. In this paper we propose a dual accelerated proximal gradient algorithm which is amenable to parallelization and demonstrate that its GPU implementation affords high speed-up values (with respect to a CPU implementation) and greatly outperforms well-established commercial optimizers such as Gurobi.
| Item Type: | Conference or Workshop Item (Speech) |
|---|---|
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Research Area: | Computer Science and Applications |
| Depositing User: | Users 44 not found. |
| Date Deposited: | 22 Oct 2015 13:41 |
| Last Modified: | 22 Oct 2015 13:41 |
| URI: | http://eprints.imtlucca.it/id/eprint/2779 |
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