کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
172765 | 458561 | 2013 | 12 صفحه PDF | دانلود رایگان |

The molecular weight distribution (MWD) is at the core of establishing key quality indices for free radical polymerization processes. Due to large-scale features of the rigorous model, consisting of a very large number of differential and algebraic equations, dynamic simulation of MWD is always challenging. A sequential variable decoupling method (SVD) has been proposed to calculate the MWD for any reasonably large chain-length number. In the current paper, parallel computing methods were developed to accelerate the MWD simulation. Both coarse-grained and fine-grained parallelism methods have been proposed. A theoretical analysis of the proposed methods was conducted to demonstrate its high efficiency in parallel computing. Both Intel multi-core-processor-based and NVIDIA graphics-processing-unit-based parallel computing platforms were implemented, achieving significant speedups in computation for MWD simulation.
► Parallel computing methods were developed to accelerate the MWD simulation.
► Theoretical analysis proves the best efficiency in parallel computing of the method.
► Coarse-grained parallelism was implemented on Intel multi-core-processor platform.
► Hybrid form parallelism was implemented on NVIDIA GPU platform.
Journal: Computers & Chemical Engineering - Volume 48, 10 January 2013, Pages 175–186