A parallel function evaluation approach for solution to large-scale equation-oriented models. (4th October 2016)

• Record Type: Journal Article
• Authors: Ma, Yannan; Shao, Zhijiang; Chen, Xi; Biegler, Lorenz T.
• Is Part Of: Computers & chemical engineering. Volume 93(2016)
• Page Start: 309
• Page End: 322
• Publication Date: 2016-10-04
• Subjects: Equation-oriented model -- Function evaluation -- Parallel computing -- GPU -- Multi-core processor; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2016.07.015
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A parallel function evaluation method was developed to accelerate numerical solution for large-scale EO models. The implementation of the method utilizes both modern multi-core processor and GPU technology. Guidelines are given for selecting applicable platforms based on the model characteristics. Abstract: The equation-oriented (EO) approach is widely used for process simulation and optimization. Nevertheless, large-scale EO models consist of a huge number of nonlinear equations and make the solution procedure a challenging and time-consuming task. For most gradient-based numerical algorithms, function evaluations are the dominant step during the solution procedure. Here, a parallel computation method is developed for function evaluations within EO optimization strategies. After dividing the equations into several groups, function evaluations are calculated by using multiple threads on a parallel hardware platform simultaneously. Theoretical analysis for the speedup ratio is conducted. The implementation of the proposed method on a multi-core processor platform as well as a graphics processing unit (GPU) platform is then presented with several case studies. Numerical results are compared and discussed to show that the multi-core processor implementation has good computational performance, whereas the GPU implementation only achieves computational acceleration under relatively specific conditions.