A hybrid CPU-Graphics Processing Unit (GPU) approach for computationally efficient simulation-optimization

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dc.contributor.author Chan, Lau Mai
dc.contributor.author Srinivasan, Rajagopalan
dc.date.accessioned 2016-04-16T16:13:17Z
dc.date.available 2016-04-16T16:13:17Z
dc.date.issued 2016-01
dc.identifier.citation Chan, Lau Mai and Srinivasan, Rajagopalan, “A hybrid CPU-Graphics Processing Unit (GPU) approach for computationally efficient simulation-optimization”, Computers & Chemical Engineering, DOI: 10.1016/j.compchemeng.2016.01.001, Jan. 2016. en_US
dc.identifier.issn 0098-1354
dc.identifier.uri http://dx.doi.org/10.1016/j.compchemeng.2016.01.001
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/2199
dc.description.abstract Simulation-optimization (Sim-Opt) is a widely used optimization technique that enables the use of simulation model so as naturally describe system complexity and stochastics. A key barrier to its broader adoption is the high computational cost associated with simulation that often limits its practicability. In this paper, we propose the use of GPU parallel computing, to enhance the computational efficiency of Sim-Opt. The main objective of this work is to develop a systematic framework that can be used to construct an efficient hybrid CPU-GPU program. The optimization of a process monitoring model using a Genetic Algorithm is used as a case study to illustrate the proposed approach. Our results show an over 100× acceleration of computation time by the developed hybrid program in comparison to a traditional CPU-based approach. en_US
dc.description.statementofresponsibility by Lau Mai Chan and Rajagopalan Srinivasan
dc.format.extent Vol. 87, pp. 49–62
dc.language.iso en_US en_US
dc.publisher Elsevier en_US
dc.subject Genetic Algorithm en_US
dc.subject Parallel computing en_US
dc.subject Sim-Opt en_US
dc.subject PCA en_US
dc.subject Tennessee Eastman challenge process en_US
dc.subject Gadget timed out while loading en_US
dc.title A hybrid CPU-Graphics Processing Unit (GPU) approach for computationally efficient simulation-optimization en_US
dc.type Article en_US
dc.relation.journal Computers & Chemical Engineering

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