Research on the Solution of Heat Exchanger Network MINLP Problems Based on GPU

The optimization of heat exchanger network can be expressed in a Mixed Integer Non-Linear mathematical Programming (MINLP) model. However, it demands huge computing power to solve a realistic heat exchanger network optimize problem. Nowadays graphic processing unit (GPU) can be very powerful for gen...

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Bibliographic Details
Published inHigh Performance Computing Vol. 207; pp. 110 - 117
Main Authors Xia, Mingxing, Ren, Yuxing, Tang, Yazhe, Kang, Lixia, Liu, Yongzhong
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2013
Springer Berlin Heidelberg
SeriesCommunications in Computer and Information Science
Subjects
CUDA
GPU
heat exchanger network
MINLP
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Summary:The optimization of heat exchanger network can be expressed in a Mixed Integer Non-Linear mathematical Programming (MINLP) model. However, it demands huge computing power to solve a realistic heat exchanger network optimize problem. Nowadays graphic processing unit (GPU) can be very powerful for general purpose computation. Based on the CUDA framework, this paper presents a parallel computing framework for solving the MINLP problem. We concentrate on both parallel computing model and specific GPU programming level optimization. Tests on a simple MINLP problem is conducted and the results show the new solution has 40 times faster than the one running serially on CPU.
ISBN:3642415903
9783642415906
ISSN:1865-0929
1865-0937
DOI:10.1007/978-3-642-41591-3_10